Eval bug: Unable to run with Qwen3 model on rocm with gfx1100, but works on cpu

[chowdri]

Name and Version

$ llama-cli --version

ggml_cuda_init: GGML_CUDA_FORCE_MMQ:    no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 2 ROCm devices:
  Device 0: Radeon RX 7900 GRE, gfx1100 (0x1100), VMM: no, Wave Size: 32
  Device 1: Radeon RX Vega, gfx900:xnack- (0x900), VMM: no, Wave Size: 64
version: 5898 (cbc68be5)
built with cc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0 for x86_64-linux-gnu

Operating systems

Linux

GGML backends

HIP

Hardware

7950X3D + 7900 GRE (gfx1100) + Vega 64 (gfx 900)

Models

Qwen3-14B-Q8_0.gguf

Problem description & steps to reproduce

$ llama-cli -m Qwen3-14B-Q8_0.gguf 
ggml_cuda_init: GGML_CUDA_FORCE_MMQ:    no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 2 ROCm devices:
  Device 0: Radeon RX 7900 GRE, gfx1100 (0x1100), VMM: no, Wave Size: 32
  Device 1: Radeon RX Vega, gfx900:xnack- (0x900), VMM: no, Wave Size: 64
build: 5898 (cbc68be5) with cc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0 for x86_64-linux-gnu
main: llama backend init
main: load the model and apply lora adapter, if any
llama_model_load_from_file_impl: using device ROCm0 (Radeon RX 7900 GRE) - 16312 MiB free
llama_model_load_from_file_impl: using device ROCm1 (Radeon RX Vega) - 8160 MiB free
llama_model_loader: loaded meta data with 27 key-value pairs and 443 tensors from Qwen3-14B-Q8_0.gguf (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv   0:                       general.architecture str              = qwen3
llama_model_loader: - kv   1:                               general.type str              = model
llama_model_loader: - kv   2:                               general.name str              = Qwen3 14B
llama_model_loader: - kv   3:                           general.basename str              = Qwen3
llama_model_loader: - kv   4:                         general.size_label str              = 14B
llama_model_loader: - kv   5:                          qwen3.block_count u32              = 40
llama_model_loader: - kv   6:                       qwen3.context_length u32              = 32768
llama_model_loader: - kv   7:                     qwen3.embedding_length u32              = 5120
llama_model_loader: - kv   8:                  qwen3.feed_forward_length u32              = 17408
llama_model_loader: - kv   9:                 qwen3.attention.head_count u32              = 40
llama_model_loader: - kv  10:              qwen3.attention.head_count_kv u32              = 8
llama_model_loader: - kv  11:                       qwen3.rope.freq_base f32              = 1000000.000000
llama_model_loader: - kv  12:     qwen3.attention.layer_norm_rms_epsilon f32              = 0.000001
llama_model_loader: - kv  13:                 qwen3.attention.key_length u32              = 128
llama_model_loader: - kv  14:               qwen3.attention.value_length u32              = 128
llama_model_loader: - kv  15:                       tokenizer.ggml.model str              = gpt2
llama_model_loader: - kv  16:                         tokenizer.ggml.pre str              = qwen2
llama_model_loader: - kv  17:                      tokenizer.ggml.tokens arr[str,151936]  = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv  18:                  tokenizer.ggml.token_type arr[i32,151936]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv  19:                      tokenizer.ggml.merges arr[str,151387]  = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
llama_model_loader: - kv  20:                tokenizer.ggml.eos_token_id u32              = 151645
llama_model_loader: - kv  21:            tokenizer.ggml.padding_token_id u32              = 151643
llama_model_loader: - kv  22:                tokenizer.ggml.bos_token_id u32              = 151643
llama_model_loader: - kv  23:               tokenizer.ggml.add_bos_token bool             = false
llama_model_loader: - kv  24:                    tokenizer.chat_template str              = {%- if tools %}\n    {{- '<|im_start|>...
llama_model_loader: - kv  25:               general.quantization_version u32              = 2
llama_model_loader: - kv  26:                          general.file_type u32              = 7
llama_model_loader: - type  f32:  161 tensors
llama_model_loader: - type q8_0:  282 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type   = Q8_0
print_info: file size   = 14.61 GiB (8.50 BPW) 
load: special tokens cache size = 26
load: token to piece cache size = 0.9311 MB
print_info: arch             = qwen3
print_info: vocab_only       = 0
print_info: n_ctx_train      = 32768
print_info: n_embd           = 5120
print_info: n_layer          = 40
print_info: n_head           = 40
print_info: n_head_kv        = 8
print_info: n_rot            = 128
print_info: n_swa            = 0
print_info: is_swa_any       = 0
print_info: n_embd_head_k    = 128
print_info: n_embd_head_v    = 128
print_info: n_gqa            = 5
print_info: n_embd_k_gqa     = 1024
print_info: n_embd_v_gqa     = 1024
print_info: f_norm_eps       = 0.0e+00
print_info: f_norm_rms_eps   = 1.0e-06
print_info: f_clamp_kqv      = 0.0e+00
print_info: f_max_alibi_bias = 0.0e+00
print_info: f_logit_scale    = 0.0e+00
print_info: f_attn_scale     = 0.0e+00
print_info: n_ff             = 17408
print_info: n_expert         = 0
print_info: n_expert_used    = 0
print_info: causal attn      = 1
print_info: pooling type     = 0
print_info: rope type        = 2
print_info: rope scaling     = linear
print_info: freq_base_train  = 1000000.0
print_info: freq_scale_train = 1
print_info: n_ctx_orig_yarn  = 32768
print_info: rope_finetuned   = unknown
print_info: model type       = 14B
print_info: model params     = 14.77 B
print_info: general.name     = Qwen3 14B
print_info: vocab type       = BPE
print_info: n_vocab          = 151936
print_info: n_merges         = 151387
print_info: BOS token        = 151643 '<|endoftext|>'
print_info: EOS token        = 151645 '<|im_end|>'
print_info: EOT token        = 151645 '<|im_end|>'
print_info: PAD token        = 151643 '<|endoftext|>'
print_info: LF token         = 198 'Ċ'
print_info: FIM PRE token    = 151659 '<|fim_prefix|>'
print_info: FIM SUF token    = 151661 '<|fim_suffix|>'
print_info: FIM MID token    = 151660 '<|fim_middle|>'
print_info: FIM PAD token    = 151662 '<|fim_pad|>'
print_info: FIM REP token    = 151663 '<|repo_name|>'
print_info: FIM SEP token    = 151664 '<|file_sep|>'
print_info: EOG token        = 151643 '<|endoftext|>'
print_info: EOG token        = 151645 '<|im_end|>'
print_info: EOG token        = 151662 '<|fim_pad|>'
print_info: EOG token        = 151663 '<|repo_name|>'
print_info: EOG token        = 151664 '<|file_sep|>'
print_info: max token length = 256
load_tensors: loading model tensors, this can take a while... (mmap = true)
load_tensors: offloading 0 repeating layers to GPU
load_tensors: offloaded 0/41 layers to GPU
load_tensors:   CPU_Mapped model buffer size = 14965.61 MiB
............................................................................................
llama_context: constructing llama_context
llama_context: n_seq_max     = 1
llama_context: n_ctx         = 4096
llama_context: n_ctx_per_seq = 4096
llama_context: n_batch       = 2048
llama_context: n_ubatch      = 512
llama_context: causal_attn   = 1
llama_context: flash_attn    = 0
llama_context: freq_base     = 1000000.0
llama_context: freq_scale    = 1
llama_context: n_ctx_per_seq (4096) < n_ctx_train (32768) -- the full capacity of the model will not be utilized
llama_context:        CPU  output buffer size =     0.58 MiB
llama_kv_cache_unified:        CPU KV buffer size =   640.00 MiB
llama_kv_cache_unified: size =  640.00 MiB (  4096 cells,  40 layers,  1 seqs), K (f16):  320.00 MiB, V (f16):  320.00 MiB
llama_kv_cache_unified: LLAMA_SET_ROWS=0, using old ggml_cpy() method for backwards compatibility
llama_context:      ROCm0 compute buffer size =  1094.99 MiB
llama_context:  ROCm_Host compute buffer size =    18.01 MiB
llama_context: graph nodes  = 1606
llama_context: graph splits = 524 (with bs=512), 121 (with bs=1)
common_init_from_params: setting dry_penalty_last_n to ctx_size = 4096
common_init_from_params: warming up the model with an empty run - please wait ... (--no-warmup to disable)
ggml_cuda_compute_forward: MUL failed
ROCm error: invalid device function
  current device: 0, in function ggml_cuda_compute_forward at /home/praful/llama.cpp/ggml/src/ggml-cuda/ggml-cuda.cu:2482
  err
/home/praful/llama.cpp/ggml/src/ggml-cuda/ggml-cuda.cu:79: ROCm error
[New LWP 626504]
[New LWP 626503]
[New LWP 626502]
[New LWP 626501]
[New LWP 626500]
[New LWP 626499]
[New LWP 626498]
[New LWP 626497]
[New LWP 626496]
[New LWP 626495]
[New LWP 626494]
[New LWP 626493]
[New LWP 626492]
[New LWP 626491]
[New LWP 626490]
[New LWP 626424]
[New LWP 626293]
[New LWP 626031]
warning: could not find '.gnu_debugaltlink' file for /lib/x86_64-linux-gnu/liblber.so.2
warning: could not find '.gnu_debugaltlink' file for /lib/x86_64-linux-gnu/libbrotlidec.so.1
warning: could not find '.gnu_debugaltlink' file for /lib/x86_64-linux-gnu/libbrotlicommon.so.1
[Thread debugging using libthread_db enabled]
Using host libthread_db library "/lib/x86_64-linux-gnu/libthread_db.so.1".
0x00007009c1b107e3 in __GI___wait4 (pid=626505, stat_loc=0x0, options=0, usage=0x0) at ../sysdeps/unix/sysv/linux/wait4.c:30
warning: 30	../sysdeps/unix/sysv/linux/wait4.c: No such file or directory
#0  0x00007009c1b107e3 in __GI___wait4 (pid=626505, stat_loc=0x0, options=0, usage=0x0) at ../sysdeps/unix/sysv/linux/wait4.c:30
30	in ../sysdeps/unix/sysv/linux/wait4.c
#1  0x00007009c218fde3 in ggml_print_backtrace () from /home/praful/llama.cpp/build/bin/libggml-base.so
#2  0x00007009c218ff8b in ggml_abort () from /home/praful/llama.cpp/build/bin/libggml-base.so
#3  0x00007009be2e7f22 in ggml_cuda_error(char const*, char const*, char const*, int, char const*) () from /home/praful/llama.cpp/build/bin/libggml-hip.so
#4  0x00007009be2eed2a in ggml_backend_cuda_graph_compute(ggml_backend*, ggml_cgraph*) () from /home/praful/llama.cpp/build/bin/libggml-hip.so
#5  0x00007009c21a7b33 in ggml_backend_sched_graph_compute_async () from /home/praful/llama.cpp/build/bin/libggml-base.so
#6  0x00007009c22b75d1 in llama_context::graph_compute(ggml_cgraph*, bool) () from /home/praful/llama.cpp/build/bin/libllama.so
#7  0x00007009c22b7c03 in llama_context::process_ubatch(llama_ubatch const&, llm_graph_type, llama_memory_context_i*, ggml_status&) () from /home/praful/llama.cpp/build/bin/libllama.so
#8  0x00007009c22bb584 in llama_context::decode(llama_batch const&) () from /home/praful/llama.cpp/build/bin/libllama.so
#9  0x00007009c22bc7df in llama_decode () from /home/praful/llama.cpp/build/bin/libllama.so
#10 0x00005ee35b50d42a in common_init_from_params(common_params&) ()
#11 0x00005ee35b4183da in main ()
[Inferior 1 (process 626028) detached]
Aborted (core dumped)

First Bad Commit

Dont know.

Relevant log output

$ echo $ROCM_PATH

/opt/rocm-6.4.1/

[chowdri]

ok I want include some more experiments.

the primary graphics adapter is gfx1100 (on pcie x16 slot) and gfx900 is secondary (on pcie x4 slot) .

upon running llama-bench I get the following:

$ llama-bench -m .lmstudio/models/lmstudio-community/Qwen3-14B-GGUF/Qwen3-14B-Q8_0.gguf 

ggml_cuda_init: GGML_CUDA_FORCE_MMQ:    no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 2 ROCm devices:
  Device 0: Radeon RX 7900 GRE, gfx1100 (0x1100), VMM: no, Wave Size: 32
  Device 1: Radeon RX Vega, gfx900:xnack- (0x900), VMM: no, Wave Size: 64
| model                          |       size |     params | backend    | ngl |            test |                  t/s |
| ------------------------------ | ---------: | ---------: | ---------- | --: | --------------: | -------------------: |
/home/praful/llama.cpp/ggml/src/ggml-cuda/ggml-cuda.cu:79: ROCm error
[New LWP 20492]
[New LWP 19320]
[Thread debugging using libthread_db enabled]
Using host libthread_db library "/lib/x86_64-linux-gnu/libthread_db.so.1".
0x00007d701c9107e3 in __GI___wait4 (pid=20819, stat_loc=0x0, options=0, usage=0x0) at ../sysdeps/unix/sysv/linux/wait4.c:30
warning: 30	../sysdeps/unix/sysv/linux/wait4.c: No such file or directory
#0  0x00007d701c9107e3 in __GI___wait4 (pid=20819, stat_loc=0x0, options=0, usage=0x0) at ../sysdeps/unix/sysv/linux/wait4.c:30
30	in ../sysdeps/unix/sysv/linux/wait4.c
#1  0x00007d701cfeade3 in ggml_print_backtrace () from /home/praful/llama.cpp/build/bin/libggml-base.so
#2  0x00007d701cfeaf8b in ggml_abort () from /home/praful/llama.cpp/build/bin/libggml-base.so
#3  0x00007d701a0e7f22 in ggml_cuda_error(char const*, char const*, char const*, int, char const*) () from /home/praful/llama.cpp/build/bin/libggml-hip.so
#4  0x00007d701a0eed2a in ggml_backend_cuda_graph_compute(ggml_backend*, ggml_cgraph*) () from /home/praful/llama.cpp/build/bin/libggml-hip.so
#5  0x00007d701d002b33 in ggml_backend_sched_graph_compute_async () from /home/praful/llama.cpp/build/bin/libggml-base.so
#6  0x00007d701d1125d1 in llama_context::graph_compute(ggml_cgraph*, bool) () from /home/praful/llama.cpp/build/bin/libllama.so
#7  0x00007d701d112c03 in llama_context::process_ubatch(llama_ubatch const&, llm_graph_type, llama_memory_context_i*, ggml_status&) () from /home/praful/llama.cpp/build/bin/libllama.so
#8  0x00007d701d116584 in llama_context::decode(llama_batch const&) () from /home/praful/llama.cpp/build/bin/libllama.so
#9  0x00007d701d1177df in llama_decode () from /home/praful/llama.cpp/build/bin/libllama.so
#10 0x00005f577da92a11 in test_prompt(llama_context*, int, int, int) ()
#11 0x00005f577da8e994 in main ()
[Inferior 1 (process 19317) detached]
Aborted (core dumped)

upon selecting gfx1100 with environment variable, I get the following:

$ export ROCR_VISIBLE_DEVICES=0

$ llama-bench -m .lmstudio/models/lmstudio-community/Qwen3-14B-GGUF/Qwen3-14B-Q8_0.gguf 
ggml_cuda_init: GGML_CUDA_FORCE_MMQ:    no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 1 ROCm devices:
  Device 0: Radeon RX 7900 GRE, gfx1100 (0x1100), VMM: no, Wave Size: 32
| model                          |       size |     params | backend    | ngl |            test |                  t/s |
| ------------------------------ | ---------: | ---------: | ---------- | --: | --------------: | -------------------: |
| qwen3 14B Q8_0                 |  14.61 GiB |    14.77 B | ROCm       |  99 |           pp512 |       1143.73 ± 3.81 |
| qwen3 14B Q8_0                 |  14.61 GiB |    14.77 B | ROCm       |  99 |           tg128 |         32.53 ± 0.12 |

build: cbc68be5 (5898)

The process is definitely running on GPU ( I checked clocks and power consumption).

upon setting device to gfx900:

$ export ROCR_VISIBLE_DEVICES=1

$ llama-bench -m .lmstudio/models/lmstudio-community/Qwen3-14B-GGUF/Qwen3-14B-Q8_0.gguf 
ggml_cuda_init: GGML_CUDA_FORCE_MMQ:    no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 1 ROCm devices:
  Device 0: Radeon RX Vega, gfx900:xnack- (0x900), VMM: no, Wave Size: 64
| model                          |       size |     params | backend    | ngl |            test |                  t/s |
| ------------------------------ | ---------: | ---------: | ---------- | --: | --------------: | -------------------: |
main: error: failed to load model '.lmstudio/models/lmstudio-community/Qwen3-14B-GGUF/Qwen3-14B-Q8_0.gguf'

This is expected because rocm does not support gfx900.

When I run llama-cli with gfx1100:

export ROCR_VISIBLE_DEVICES=0

$llama-cli -m .lmstudio/models/lmstudio-community/Qwen3-14B-GGUF/Qwen3-14B-Q8_0.gguf 

ggml_cuda_init: GGML_CUDA_FORCE_MMQ:    no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 1 ROCm devices:
  Device 0: Radeon RX 7900 GRE, gfx1100 (0x1100), VMM: no, Wave Size: 32
build: 5898 (cbc68be5) with cc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0 for x86_64-linux-gnu
main: llama backend init
main: load the model and apply lora adapter, if any
llama_model_load_from_file_impl: using device ROCm0 (Radeon RX 7900 GRE) - 16312 MiB free
llama_model_loader: loaded meta data with 27 key-value pairs and 443 tensors from .lmstudio/models/lmstudio-community/Qwen3-14B-GGUF/Qwen3-14B-Q8_0.gguf (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv   0:                       general.architecture str              = qwen3
llama_model_loader: - kv   1:                               general.type str              = model
llama_model_loader: - kv   2:                               general.name str              = Qwen3 14B
llama_model_loader: - kv   3:                           general.basename str              = Qwen3
llama_model_loader: - kv   4:                         general.size_label str              = 14B
llama_model_loader: - kv   5:                          qwen3.block_count u32              = 40
llama_model_loader: - kv   6:                       qwen3.context_length u32              = 32768
llama_model_loader: - kv   7:                     qwen3.embedding_length u32              = 5120
llama_model_loader: - kv   8:                  qwen3.feed_forward_length u32              = 17408
llama_model_loader: - kv   9:                 qwen3.attention.head_count u32              = 40
llama_model_loader: - kv  10:              qwen3.attention.head_count_kv u32              = 8
llama_model_loader: - kv  11:                       qwen3.rope.freq_base f32              = 1000000.000000
llama_model_loader: - kv  12:     qwen3.attention.layer_norm_rms_epsilon f32              = 0.000001
llama_model_loader: - kv  13:                 qwen3.attention.key_length u32              = 128
llama_model_loader: - kv  14:               qwen3.attention.value_length u32              = 128
llama_model_loader: - kv  15:                       tokenizer.ggml.model str              = gpt2
llama_model_loader: - kv  16:                         tokenizer.ggml.pre str              = qwen2
llama_model_loader: - kv  17:                      tokenizer.ggml.tokens arr[str,151936]  = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv  18:                  tokenizer.ggml.token_type arr[i32,151936]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv  19:                      tokenizer.ggml.merges arr[str,151387]  = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
llama_model_loader: - kv  20:                tokenizer.ggml.eos_token_id u32              = 151645
llama_model_loader: - kv  21:            tokenizer.ggml.padding_token_id u32              = 151643
llama_model_loader: - kv  22:                tokenizer.ggml.bos_token_id u32              = 151643
llama_model_loader: - kv  23:               tokenizer.ggml.add_bos_token bool             = false
llama_model_loader: - kv  24:                    tokenizer.chat_template str              = {%- if tools %}\n    {{- '<|im_start|>...
llama_model_loader: - kv  25:               general.quantization_version u32              = 2
llama_model_loader: - kv  26:                          general.file_type u32              = 7
llama_model_loader: - type  f32:  161 tensors
llama_model_loader: - type q8_0:  282 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type   = Q8_0
print_info: file size   = 14.61 GiB (8.50 BPW) 
load: special tokens cache size = 26
load: token to piece cache size = 0.9311 MB
print_info: arch             = qwen3
print_info: vocab_only       = 0
print_info: n_ctx_train      = 32768
print_info: n_embd           = 5120
print_info: n_layer          = 40
print_info: n_head           = 40
print_info: n_head_kv        = 8
print_info: n_rot            = 128
print_info: n_swa            = 0
print_info: is_swa_any       = 0
print_info: n_embd_head_k    = 128
print_info: n_embd_head_v    = 128
print_info: n_gqa            = 5
print_info: n_embd_k_gqa     = 1024
print_info: n_embd_v_gqa     = 1024
print_info: f_norm_eps       = 0.0e+00
print_info: f_norm_rms_eps   = 1.0e-06
print_info: f_clamp_kqv      = 0.0e+00
print_info: f_max_alibi_bias = 0.0e+00
print_info: f_logit_scale    = 0.0e+00
print_info: f_attn_scale     = 0.0e+00
print_info: n_ff             = 17408
print_info: n_expert         = 0
print_info: n_expert_used    = 0
print_info: causal attn      = 1
print_info: pooling type     = 0
print_info: rope type        = 2
print_info: rope scaling     = linear
print_info: freq_base_train  = 1000000.0
print_info: freq_scale_train = 1
print_info: n_ctx_orig_yarn  = 32768
print_info: rope_finetuned   = unknown
print_info: model type       = 14B
print_info: model params     = 14.77 B
print_info: general.name     = Qwen3 14B
print_info: vocab type       = BPE
print_info: n_vocab          = 151936
print_info: n_merges         = 151387
print_info: BOS token        = 151643 '<|endoftext|>'
print_info: EOS token        = 151645 '<|im_end|>'
print_info: EOT token        = 151645 '<|im_end|>'
print_info: PAD token        = 151643 '<|endoftext|>'
print_info: LF token         = 198 'Ċ'
print_info: FIM PRE token    = 151659 '<|fim_prefix|>'
print_info: FIM SUF token    = 151661 '<|fim_suffix|>'
print_info: FIM MID token    = 151660 '<|fim_middle|>'
print_info: FIM PAD token    = 151662 '<|fim_pad|>'
print_info: FIM REP token    = 151663 '<|repo_name|>'
print_info: FIM SEP token    = 151664 '<|file_sep|>'
print_info: EOG token        = 151643 '<|endoftext|>'
print_info: EOG token        = 151645 '<|im_end|>'
print_info: EOG token        = 151662 '<|fim_pad|>'
print_info: EOG token        = 151663 '<|repo_name|>'
print_info: EOG token        = 151664 '<|file_sep|>'
print_info: max token length = 256
load_tensors: loading model tensors, this can take a while... (mmap = true)
load_tensors: offloading 0 repeating layers to GPU
load_tensors: offloaded 0/41 layers to GPU
load_tensors:   CPU_Mapped model buffer size = 14965.61 MiB
............................................................................................
llama_context: constructing llama_context
llama_context: n_seq_max     = 1
llama_context: n_ctx         = 4096
llama_context: n_ctx_per_seq = 4096
llama_context: n_batch       = 2048
llama_context: n_ubatch      = 512
llama_context: causal_attn   = 1
llama_context: flash_attn    = 0
llama_context: freq_base     = 1000000.0
llama_context: freq_scale    = 1
llama_context: n_ctx_per_seq (4096) < n_ctx_train (32768) -- the full capacity of the model will not be utilized
llama_context:        CPU  output buffer size =     0.58 MiB
llama_kv_cache_unified:        CPU KV buffer size =   640.00 MiB
llama_kv_cache_unified: size =  640.00 MiB (  4096 cells,  40 layers,  1 seqs), K (f16):  320.00 MiB, V (f16):  320.00 MiB
llama_kv_cache_unified: LLAMA_SET_ROWS=0, using old ggml_cpy() method for backwards compatibility
llama_context:      ROCm0 compute buffer size =  1094.99 MiB
llama_context:  ROCm_Host compute buffer size =    18.01 MiB
llama_context: graph nodes  = 1606
llama_context: graph splits = 524 (with bs=512), 121 (with bs=1)
common_init_from_params: setting dry_penalty_last_n to ctx_size = 4096
common_init_from_params: warming up the model with an empty run - please wait ... (--no-warmup to disable)
main: llama threadpool init, n_threads = 16
main: chat template is available, enabling conversation mode (disable it with -no-cnv)
main: chat template example:
<|im_start|>system
You are a helpful assistant<|im_end|>
<|im_start|>user
Hello<|im_end|>
<|im_start|>assistant
Hi there<|im_end|>
<|im_start|>user
How are you?<|im_end|>
<|im_start|>assistant


system_info: n_threads = 16 (n_threads_batch = 16) / 32 | ROCm : NO_VMM = 1 | PEER_MAX_BATCH_SIZE = 128 | CPU : SSE3 = 1 | SSSE3 = 1 | AVX = 1 | AVX2 = 1 | F16C = 1 | FMA = 1 | BMI2 = 1 | AVX512 = 1 | AVX512_VBMI = 1 | AVX512_VNNI = 1 | AVX512_BF16 = 1 | LLAMAFILE = 1 | OPENMP = 1 | REPACK = 1 | 

main: interactive mode on.
sampler seed: 813641237
sampler params: 
	repeat_last_n = 64, repeat_penalty = 1.000, frequency_penalty = 0.000, presence_penalty = 0.000
	dry_multiplier = 0.000, dry_base = 1.750, dry_allowed_length = 2, dry_penalty_last_n = 4096
	top_k = 40, top_p = 0.950, min_p = 0.050, xtc_probability = 0.000, xtc_threshold = 0.100, typical_p = 1.000, top_n_sigma = -1.000, temp = 0.800
	mirostat = 0, mirostat_lr = 0.100, mirostat_ent = 5.000
sampler chain: logits -> logit-bias -> penalties -> dry -> top-n-sigma -> top-k -> typical -> top-p -> min-p -> xtc -> temp-ext -> dist 
generate: n_ctx = 4096, n_batch = 2048, n_predict = -1, n_keep = 0

== Running in interactive mode. ==
 - Press Ctrl+C to interject at any time.
 - Press Return to return control to the AI.
 - To return control without starting a new line, end your input with '/'.
 - If you want to submit another line, end your input with '\'.
 - Not using system message. To change it, set a different value via -sys PROMPT


> 

however, while the program works, the inference is performed by the cpu and not the gpu. How to offload all work to GPU?

[CsBigDataHub]

Same here

docker run --rm --label ai.ramalama.model=llama3.2:3b --label ai.ramalama.engine=docker --label ai.ramalama.runtime=llama.cpp --label ai.ramalama.port=8080 --label ai.ramalama.command=run --device /dev/dri --device /dev/kfd -e HIP_VISIBLE_DEVICES=1 -p 8080:8080 --security-opt=label=disable --cap-drop=all --security-opt=no-new-privileges -t -i --label ai.ramalama --name ramalama_IGngq1HF2u --env=HOME=/tmp --init --mount=type=bind,src=/home/mypc/.local/share/ramalama/store/ollama/library/llama3.2/blobs/sha256-dde5aa3fc5ffc17176b5e8bdc82f587b24b2678c6c66101bf7da77af9f7ccdff,destination=/mnt/models/llama3.2,ro --mount=type=bind,src=/home/mypc/.local/share/ramalama/store/ollama/library/llama3.2/blobs/sha256-34bb5ab01051a11372a91f95f3fbbc51173eed8e7f13ec395b9ae9b8bd0e242b,destination=/mnt/models/config.json,ro --mount=type=bind,src=/home/mypc/.local/share/ramalama/store/ollama/library/llama3.2/blobs/sha256-966de95ca8a62200913e3f8bfbf84c8494536f1b94b49166851e76644e966396,destination=/mnt/models/chat_template,ro quay.io/ramalama/rocm:latest llama-server --port 8080 --model /mnt/models/llama3.2 --no-warmup --jinja --log-colors --alias llama3.2:3b --ctx-size 2048 --temp 0.8 --cache-reuse 256 -v -ngl 999 --threads 12 --host 0.0.0.0 

ggml_cuda_init: GGML_CUDA_FORCE_MMQ:    no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 1 ROCm devices:
  Device 0: AMD Radeon Graphics, gfx1036 (0x1036), VMM: no, Wave Size: 32
build: 5764 (f667f1e6) with cc (GCC) 15.1.1 20250521 (Red Hat 15.1.1-2) for x86_64-redhat-linux
system info: n_threads = 12, n_threads_batch = 12, total_threads = 24

system_info: n_threads = 12 (n_threads_batch = 12) / 24 | ROCm : NO_VMM = 1 | PEER_MAX_BATCH_SIZE = 128 | CPU : SSE3 = 1 | SSSE3 = 1 | AVX = 1 | AVX2 = 1 | F16C = 1 | FMA = 1 | BMI2 = 1 | LLAMAFILE = 1 | OPENMP = 1 | REPACK = 1 | 

main: binding port with default address family
main: HTTP server is listening, hostname: 0.0.0.0, port: 8080, http threads: 23
main: loading model
srv    load_model: loading model '/mnt/models/llama3.2'
llama_model_load_from_file_impl: using device ROCm0 (AMD Radeon Graphics) - 31668 MiB free
llama_model_loader: loaded meta data with 30 key-value pairs and 255 tensors from /mnt/models/llama3.2 (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv   0:                       general.architecture str              = llama
llama_model_loader: - kv   1:                               general.type str              = model
llama_model_loader: - kv   2:                               general.name str              = Llama 3.2 3B Instruct
llama_model_loader: - kv   3:                           general.finetune str              = Instruct
llama_model_loader: - kv   4:                           general.basename str              = Llama-3.2
llama_model_loader: - kv   5:                         general.size_label str              = 3B
llama_model_loader: - kv   6:                               general.tags arr[str,6]       = ["facebook", "meta", "pytorch", "llam...
llama_model_loader: - kv   7:                          general.languages arr[str,8]       = ["en", "de", "fr", "it", "pt", "hi", ...
llama_model_loader: - kv   8:                          llama.block_count u32              = 28
llama_model_loader: - kv   9:                       llama.context_length u32              = 131072
llama_model_loader: - kv  10:                     llama.embedding_length u32              = 3072
llama_model_loader: - kv  11:                  llama.feed_forward_length u32              = 8192
llama_model_loader: - kv  12:                 llama.attention.head_count u32              = 24
llama_model_loader: - kv  13:              llama.attention.head_count_kv u32              = 8
llama_model_loader: - kv  14:                       llama.rope.freq_base f32              = 500000.000000
llama_model_loader: - kv  15:     llama.attention.layer_norm_rms_epsilon f32              = 0.000010
llama_model_loader: - kv  16:                 llama.attention.key_length u32              = 128
llama_model_loader: - kv  17:               llama.attention.value_length u32              = 128
llama_model_loader: - kv  18:                          general.file_type u32              = 15
llama_model_loader: - kv  19:                           llama.vocab_size u32              = 128256
llama_model_loader: - kv  20:                 llama.rope.dimension_count u32              = 128
llama_model_loader: - kv  21:                       tokenizer.ggml.model str              = gpt2
llama_model_loader: - kv  22:                         tokenizer.ggml.pre str              = llama-bpe
llama_model_loader: - kv  23:                      tokenizer.ggml.tokens arr[str,128256]  = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv  24:                  tokenizer.ggml.token_type arr[i32,128256]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv  25:                      tokenizer.ggml.merges arr[str,280147]  = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "...
llama_model_loader: - kv  26:                tokenizer.ggml.bos_token_id u32              = 128000
llama_model_loader: - kv  27:                tokenizer.ggml.eos_token_id u32              = 128009
llama_model_loader: - kv  28:                    tokenizer.chat_template str              = {{- bos_token }}\n{%- if custom_tools ...
llama_model_loader: - kv  29:               general.quantization_version u32              = 2
llama_model_loader: - type  f32:   58 tensors
llama_model_loader: - type q4_K:  168 tensors
llama_model_loader: - type q6_K:   29 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type   = Q4_K - Medium
print_info: file size   = 1.87 GiB (5.01 BPW) 
init_tokenizer: initializing tokenizer for type 2
load: control token: 128254 '<|reserved_special_token_246|>' is not marked as EOG
load: control token: 128249 '<|reserved_special_token_241|>' is not marked as EOG
load: control token: 128246 '<|reserved_special_token_238|>' is not marked as EOG
load: control token: 128243 '<|reserved_special_token_235|>' is not marked as EOG
load: control token: 128242 '<|reserved_special_token_234|>' is not marked as EOG
load: control token: 128241 '<|reserved_special_token_233|>' is not marked as EOG
load: control token: 128240 '<|reserved_special_token_232|>' is not marked as EOG
load: control token: 128235 '<|reserved_special_token_227|>' is not marked as EOG
load: control token: 128231 '<|reserved_special_token_223|>' is not marked as EOG
load: control token: 128230 '<|reserved_special_token_222|>' is not marked as EOG
load: control token: 128228 '<|reserved_special_token_220|>' is not marked as EOG
load: control token: 128225 '<|reserved_special_token_217|>' is not marked as EOG
load: control token: 128218 '<|reserved_special_token_210|>' is not marked as EOG
load: control token: 128214 '<|reserved_special_token_206|>' is not marked as EOG
load: control token: 128213 '<|reserved_special_token_205|>' is not marked as EOG
load: control token: 128207 '<|reserved_special_token_199|>' is not marked as EOG
load: control token: 128206 '<|reserved_special_token_198|>' is not marked as EOG
load: control token: 128204 '<|reserved_special_token_196|>' is not marked as EOG
load: control token: 128200 '<|reserved_special_token_192|>' is not marked as EOG
load: control token: 128199 '<|reserved_special_token_191|>' is not marked as EOG
load: control token: 128198 '<|reserved_special_token_190|>' is not marked as EOG
load: control token: 128196 '<|reserved_special_token_188|>' is not marked as EOG
load: control token: 128194 '<|reserved_special_token_186|>' is not marked as EOG
load: control token: 128193 '<|reserved_special_token_185|>' is not marked as EOG
load: control token: 128188 '<|reserved_special_token_180|>' is not marked as EOG
load: control token: 128187 '<|reserved_special_token_179|>' is not marked as EOG
load: control token: 128185 '<|reserved_special_token_177|>' is not marked as EOG
load: control token: 128184 '<|reserved_special_token_176|>' is not marked as EOG
load: control token: 128180 '<|reserved_special_token_172|>' is not marked as EOG
load: control token: 128179 '<|reserved_special_token_171|>' is not marked as EOG
load: control token: 128178 '<|reserved_special_token_170|>' is not marked as EOG
load: control token: 128177 '<|reserved_special_token_169|>' is not marked as EOG
load: control token: 128176 '<|reserved_special_token_168|>' is not marked as EOG
load: control token: 128175 '<|reserved_special_token_167|>' is not marked as EOG
load: control token: 128171 '<|reserved_special_token_163|>' is not marked as EOG
load: control token: 128170 '<|reserved_special_token_162|>' is not marked as EOG
load: control token: 128169 '<|reserved_special_token_161|>' is not marked as EOG
load: control token: 128168 '<|reserved_special_token_160|>' is not marked as EOG
load: control token: 128165 '<|reserved_special_token_157|>' is not marked as EOG
load: control token: 128162 '<|reserved_special_token_154|>' is not marked as EOG
load: control token: 128158 '<|reserved_special_token_150|>' is not marked as EOG
load: control token: 128156 '<|reserved_special_token_148|>' is not marked as EOG
load: control token: 128155 '<|reserved_special_token_147|>' is not marked as EOG
load: control token: 128154 '<|reserved_special_token_146|>' is not marked as EOG
load: control token: 128151 '<|reserved_special_token_143|>' is not marked as EOG
load: control token: 128149 '<|reserved_special_token_141|>' is not marked as EOG
load: control token: 128147 '<|reserved_special_token_139|>' is not marked as EOG
load: control token: 128146 '<|reserved_special_token_138|>' is not marked as EOG
load: control token: 128144 '<|reserved_special_token_136|>' is not marked as EOG
load: control token: 128142 '<|reserved_special_token_134|>' is not marked as EOG
load: control token: 128141 '<|reserved_special_token_133|>' is not marked as EOG
load: control token: 128138 '<|reserved_special_token_130|>' is not marked as EOG
load: control token: 128136 '<|reserved_special_token_128|>' is not marked as EOG
load: control token: 128135 '<|reserved_special_token_127|>' is not marked as EOG
load: control token: 128134 '<|reserved_special_token_126|>' is not marked as EOG
load: control token: 128133 '<|reserved_special_token_125|>' is not marked as EOG
load: control token: 128131 '<|reserved_special_token_123|>' is not marked as EOG
load: control token: 128128 '<|reserved_special_token_120|>' is not marked as EOG
load: control token: 128124 '<|reserved_special_token_116|>' is not marked as EOG
load: control token: 128123 '<|reserved_special_token_115|>' is not marked as EOG
load: control token: 128122 '<|reserved_special_token_114|>' is not marked as EOG
load: control token: 128119 '<|reserved_special_token_111|>' is not marked as EOG
load: control token: 128115 '<|reserved_special_token_107|>' is not marked as EOG
load: control token: 128112 '<|reserved_special_token_104|>' is not marked as EOG
load: control token: 128110 '<|reserved_special_token_102|>' is not marked as EOG
load: control token: 128109 '<|reserved_special_token_101|>' is not marked as EOG
load: control token: 128108 '<|reserved_special_token_100|>' is not marked as EOG
load: control token: 128106 '<|reserved_special_token_98|>' is not marked as EOG
load: control token: 128103 '<|reserved_special_token_95|>' is not marked as EOG
load: control token: 128102 '<|reserved_special_token_94|>' is not marked as EOG
load: control token: 128101 '<|reserved_special_token_93|>' is not marked as EOG
load: control token: 128097 '<|reserved_special_token_89|>' is not marked as EOG
load: control token: 128091 '<|reserved_special_token_83|>' is not marked as EOG
load: control token: 128090 '<|reserved_special_token_82|>' is not marked as EOG
load: control token: 128089 '<|reserved_special_token_81|>' is not marked as EOG
load: control token: 128087 '<|reserved_special_token_79|>' is not marked as EOG
load: control token: 128085 '<|reserved_special_token_77|>' is not marked as EOG
load: control token: 128081 '<|reserved_special_token_73|>' is not marked as EOG
load: control token: 128078 '<|reserved_special_token_70|>' is not marked as EOG
load: control token: 128076 '<|reserved_special_token_68|>' is not marked as EOG
load: control token: 128075 '<|reserved_special_token_67|>' is not marked as EOG
load: control token: 128073 '<|reserved_special_token_65|>' is not marked as EOG
load: control token: 128068 '<|reserved_special_token_60|>' is not marked as EOG
load: control token: 128067 '<|reserved_special_token_59|>' is not marked as EOG
load: control token: 128065 '<|reserved_special_token_57|>' is not marked as EOG
load: control token: 128063 '<|reserved_special_token_55|>' is not marked as EOG
load: control token: 128062 '<|reserved_special_token_54|>' is not marked as EOG
load: control token: 128060 '<|reserved_special_token_52|>' is not marked as EOG
load: control token: 128059 '<|reserved_special_token_51|>' is not marked as EOG
load: control token: 128057 '<|reserved_special_token_49|>' is not marked as EOG
load: control token: 128054 '<|reserved_special_token_46|>' is not marked as EOG
load: control token: 128046 '<|reserved_special_token_38|>' is not marked as EOG
load: control token: 128045 '<|reserved_special_token_37|>' is not marked as EOG
load: control token: 128044 '<|reserved_special_token_36|>' is not marked as EOG
load: control token: 128043 '<|reserved_special_token_35|>' is not marked as EOG
load: control token: 128038 '<|reserved_special_token_30|>' is not marked as EOG
load: control token: 128036 '<|reserved_special_token_28|>' is not marked as EOG
load: control token: 128035 '<|reserved_special_token_27|>' is not marked as EOG
load: control token: 128032 '<|reserved_special_token_24|>' is not marked as EOG
load: control token: 128028 '<|reserved_special_token_20|>' is not marked as EOG
load: control token: 128027 '<|reserved_special_token_19|>' is not marked as EOG
load: control token: 128024 '<|reserved_special_token_16|>' is not marked as EOG
load: control token: 128023 '<|reserved_special_token_15|>' is not marked as EOG
load: control token: 128022 '<|reserved_special_token_14|>' is not marked as EOG
load: control token: 128021 '<|reserved_special_token_13|>' is not marked as EOG
load: control token: 128018 '<|reserved_special_token_10|>' is not marked as EOG
load: control token: 128016 '<|reserved_special_token_8|>' is not marked as EOG
load: control token: 128015 '<|reserved_special_token_7|>' is not marked as EOG
load: control token: 128013 '<|reserved_special_token_5|>' is not marked as EOG
load: control token: 128011 '<|reserved_special_token_3|>' is not marked as EOG
load: control token: 128005 '<|reserved_special_token_2|>' is not marked as EOG
load: control token: 128004 '<|finetune_right_pad_id|>' is not marked as EOG
load: control token: 128002 '<|reserved_special_token_0|>' is not marked as EOG
load: control token: 128252 '<|reserved_special_token_244|>' is not marked as EOG
load: control token: 128190 '<|reserved_special_token_182|>' is not marked as EOG
load: control token: 128183 '<|reserved_special_token_175|>' is not marked as EOG
load: control token: 128137 '<|reserved_special_token_129|>' is not marked as EOG
load: control token: 128182 '<|reserved_special_token_174|>' is not marked as EOG
load: control token: 128040 '<|reserved_special_token_32|>' is not marked as EOG
load: control token: 128048 '<|reserved_special_token_40|>' is not marked as EOG
load: control token: 128092 '<|reserved_special_token_84|>' is not marked as EOG
load: control token: 128215 '<|reserved_special_token_207|>' is not marked as EOG
load: control token: 128107 '<|reserved_special_token_99|>' is not marked as EOG
load: control token: 128208 '<|reserved_special_token_200|>' is not marked as EOG
load: control token: 128145 '<|reserved_special_token_137|>' is not marked as EOG
load: control token: 128031 '<|reserved_special_token_23|>' is not marked as EOG
load: control token: 128129 '<|reserved_special_token_121|>' is not marked as EOG
load: control token: 128201 '<|reserved_special_token_193|>' is not marked as EOG
load: control token: 128074 '<|reserved_special_token_66|>' is not marked as EOG
load: control token: 128095 '<|reserved_special_token_87|>' is not marked as EOG
load: control token: 128186 '<|reserved_special_token_178|>' is not marked as EOG
load: control token: 128143 '<|reserved_special_token_135|>' is not marked as EOG
load: control token: 128229 '<|reserved_special_token_221|>' is not marked as EOG
load: control token: 128007 '<|end_header_id|>' is not marked as EOG
load: control token: 128055 '<|reserved_special_token_47|>' is not marked as EOG
load: control token: 128056 '<|reserved_special_token_48|>' is not marked as EOG
load: control token: 128061 '<|reserved_special_token_53|>' is not marked as EOG
load: control token: 128153 '<|reserved_special_token_145|>' is not marked as EOG
load: control token: 128152 '<|reserved_special_token_144|>' is not marked as EOG
load: control token: 128212 '<|reserved_special_token_204|>' is not marked as EOG
load: control token: 128172 '<|reserved_special_token_164|>' is not marked as EOG
load: control token: 128160 '<|reserved_special_token_152|>' is not marked as EOG
load: control token: 128041 '<|reserved_special_token_33|>' is not marked as EOG
load: control token: 128181 '<|reserved_special_token_173|>' is not marked as EOG
load: control token: 128094 '<|reserved_special_token_86|>' is not marked as EOG
load: control token: 128118 '<|reserved_special_token_110|>' is not marked as EOG
load: control token: 128236 '<|reserved_special_token_228|>' is not marked as EOG
load: control token: 128148 '<|reserved_special_token_140|>' is not marked as EOG
load: control token: 128042 '<|reserved_special_token_34|>' is not marked as EOG
load: control token: 128139 '<|reserved_special_token_131|>' is not marked as EOG
load: control token: 128173 '<|reserved_special_token_165|>' is not marked as EOG
load: control token: 128239 '<|reserved_special_token_231|>' is not marked as EOG
load: control token: 128157 '<|reserved_special_token_149|>' is not marked as EOG
load: control token: 128052 '<|reserved_special_token_44|>' is not marked as EOG
load: control token: 128026 '<|reserved_special_token_18|>' is not marked as EOG
load: control token: 128003 '<|reserved_special_token_1|>' is not marked as EOG
load: control token: 128019 '<|reserved_special_token_11|>' is not marked as EOG
load: control token: 128116 '<|reserved_special_token_108|>' is not marked as EOG
load: control token: 128161 '<|reserved_special_token_153|>' is not marked as EOG
load: control token: 128226 '<|reserved_special_token_218|>' is not marked as EOG
load: control token: 128159 '<|reserved_special_token_151|>' is not marked as EOG
load: control token: 128012 '<|reserved_special_token_4|>' is not marked as EOG
load: control token: 128088 '<|reserved_special_token_80|>' is not marked as EOG
load: control token: 128163 '<|reserved_special_token_155|>' is not marked as EOG
load: control token: 128113 '<|reserved_special_token_105|>' is not marked as EOG
load: control token: 128250 '<|reserved_special_token_242|>' is not marked as EOG
load: control token: 128125 '<|reserved_special_token_117|>' is not marked as EOG
load: control token: 128053 '<|reserved_special_token_45|>' is not marked as EOG
load: control token: 128224 '<|reserved_special_token_216|>' is not marked as EOG
load: control token: 128247 '<|reserved_special_token_239|>' is not marked as EOG
load: control token: 128251 '<|reserved_special_token_243|>' is not marked as EOG
load: control token: 128216 '<|reserved_special_token_208|>' is not marked as EOG
load: control token: 128006 '<|start_header_id|>' is not marked as EOG
load: control token: 128211 '<|reserved_special_token_203|>' is not marked as EOG
load: control token: 128077 '<|reserved_special_token_69|>' is not marked as EOG
load: control token: 128237 '<|reserved_special_token_229|>' is not marked as EOG
load: control token: 128086 '<|reserved_special_token_78|>' is not marked as EOG
load: control token: 128227 '<|reserved_special_token_219|>' is not marked as EOG
load: control token: 128058 '<|reserved_special_token_50|>' is not marked as EOG
load: control token: 128100 '<|reserved_special_token_92|>' is not marked as EOG
load: control token: 128209 '<|reserved_special_token_201|>' is not marked as EOG
load: control token: 128084 '<|reserved_special_token_76|>' is not marked as EOG
load: control token: 128071 '<|reserved_special_token_63|>' is not marked as EOG
load: control token: 128070 '<|reserved_special_token_62|>' is not marked as EOG
load: control token: 128049 '<|reserved_special_token_41|>' is not marked as EOG
load: control token: 128197 '<|reserved_special_token_189|>' is not marked as EOG
load: control token: 128072 '<|reserved_special_token_64|>' is not marked as EOG
load: control token: 128000 '<|begin_of_text|>' is not marked as EOG
load: control token: 128223 '<|reserved_special_token_215|>' is not marked as EOG
load: control token: 128217 '<|reserved_special_token_209|>' is not marked as EOG
load: control token: 128111 '<|reserved_special_token_103|>' is not marked as EOG
load: control token: 128203 '<|reserved_special_token_195|>' is not marked as EOG
load: control token: 128051 '<|reserved_special_token_43|>' is not marked as EOG
load: control token: 128030 '<|reserved_special_token_22|>' is not marked as EOG
load: control token: 128117 '<|reserved_special_token_109|>' is not marked as EOG
load: control token: 128010 '<|python_tag|>' is not marked as EOG
load: control token: 128238 '<|reserved_special_token_230|>' is not marked as EOG
load: control token: 128255 '<|reserved_special_token_247|>' is not marked as EOG
load: control token: 128202 '<|reserved_special_token_194|>' is not marked as EOG
load: control token: 128132 '<|reserved_special_token_124|>' is not marked as EOG
load: control token: 128248 '<|reserved_special_token_240|>' is not marked as EOG
load: control token: 128167 '<|reserved_special_token_159|>' is not marked as EOG
load: control token: 128127 '<|reserved_special_token_119|>' is not marked as EOG
load: control token: 128105 '<|reserved_special_token_97|>' is not marked as EOG
load: control token: 128039 '<|reserved_special_token_31|>' is not marked as EOG
load: control token: 128232 '<|reserved_special_token_224|>' is not marked as EOG
load: control token: 128166 '<|reserved_special_token_158|>' is not marked as EOG
load: control token: 128130 '<|reserved_special_token_122|>' is not marked as EOG
load: control token: 128114 '<|reserved_special_token_106|>' is not marked as EOG
load: control token: 128234 '<|reserved_special_token_226|>' is not marked as EOG
load: control token: 128191 '<|reserved_special_token_183|>' is not marked as EOG
load: control token: 128064 '<|reserved_special_token_56|>' is not marked as EOG
load: control token: 128140 '<|reserved_special_token_132|>' is not marked as EOG
load: control token: 128096 '<|reserved_special_token_88|>' is not marked as EOG
load: control token: 128098 '<|reserved_special_token_90|>' is not marked as EOG
load: control token: 128192 '<|reserved_special_token_184|>' is not marked as EOG
load: control token: 128093 '<|reserved_special_token_85|>' is not marked as EOG
load: control token: 128150 '<|reserved_special_token_142|>' is not marked as EOG
load: control token: 128222 '<|reserved_special_token_214|>' is not marked as EOG
load: control token: 128233 '<|reserved_special_token_225|>' is not marked as EOG
load: control token: 128220 '<|reserved_special_token_212|>' is not marked as EOG
load: control token: 128034 '<|reserved_special_token_26|>' is not marked as EOG
load: control token: 128033 '<|reserved_special_token_25|>' is not marked as EOG
load: control token: 128253 '<|reserved_special_token_245|>' is not marked as EOG
load: control token: 128195 '<|reserved_special_token_187|>' is not marked as EOG
load: control token: 128099 '<|reserved_special_token_91|>' is not marked as EOG
load: control token: 128189 '<|reserved_special_token_181|>' is not marked as EOG
load: control token: 128210 '<|reserved_special_token_202|>' is not marked as EOG
load: control token: 128174 '<|reserved_special_token_166|>' is not marked as EOG
load: control token: 128083 '<|reserved_special_token_75|>' is not marked as EOG
load: control token: 128080 '<|reserved_special_token_72|>' is not marked as EOG
load: control token: 128104 '<|reserved_special_token_96|>' is not marked as EOG
load: control token: 128082 '<|reserved_special_token_74|>' is not marked as EOG
load: control token: 128219 '<|reserved_special_token_211|>' is not marked as EOG
load: control token: 128017 '<|reserved_special_token_9|>' is not marked as EOG
load: control token: 128050 '<|reserved_special_token_42|>' is not marked as EOG
load: control token: 128205 '<|reserved_special_token_197|>' is not marked as EOG
load: control token: 128047 '<|reserved_special_token_39|>' is not marked as EOG
load: control token: 128164 '<|reserved_special_token_156|>' is not marked as EOG
load: control token: 128020 '<|reserved_special_token_12|>' is not marked as EOG
load: control token: 128069 '<|reserved_special_token_61|>' is not marked as EOG
load: control token: 128245 '<|reserved_special_token_237|>' is not marked as EOG
load: control token: 128121 '<|reserved_special_token_113|>' is not marked as EOG
load: control token: 128079 '<|reserved_special_token_71|>' is not marked as EOG
load: control token: 128037 '<|reserved_special_token_29|>' is not marked as EOG
load: control token: 128244 '<|reserved_special_token_236|>' is not marked as EOG
load: control token: 128029 '<|reserved_special_token_21|>' is not marked as EOG
load: control token: 128221 '<|reserved_special_token_213|>' is not marked as EOG
load: control token: 128066 '<|reserved_special_token_58|>' is not marked as EOG
load: control token: 128120 '<|reserved_special_token_112|>' is not marked as EOG
load: control token: 128014 '<|reserved_special_token_6|>' is not marked as EOG
load: control token: 128025 '<|reserved_special_token_17|>' is not marked as EOG
load: control token: 128126 '<|reserved_special_token_118|>' is not marked as EOG
load: special tokens cache size = 256
load: token to piece cache size = 0.7999 MB
print_info: arch             = llama
print_info: vocab_only       = 0
print_info: n_ctx_train      = 131072
print_info: n_embd           = 3072
print_info: n_layer          = 28
print_info: n_head           = 24
print_info: n_head_kv        = 8
print_info: n_rot            = 128
print_info: n_swa            = 0
print_info: is_swa_any       = 0
print_info: n_embd_head_k    = 128
print_info: n_embd_head_v    = 128
print_info: n_gqa            = 3
print_info: n_embd_k_gqa     = 1024
print_info: n_embd_v_gqa     = 1024
print_info: f_norm_eps       = 0.0e+00
print_info: f_norm_rms_eps   = 1.0e-05
print_info: f_clamp_kqv      = 0.0e+00
print_info: f_max_alibi_bias = 0.0e+00
print_info: f_logit_scale    = 0.0e+00
print_info: f_attn_scale     = 0.0e+00
print_info: n_ff             = 8192
print_info: n_expert         = 0
print_info: n_expert_used    = 0
print_info: causal attn      = 1
print_info: pooling type     = 0
print_info: rope type        = 0
print_info: rope scaling     = linear
print_info: freq_base_train  = 500000.0
print_info: freq_scale_train = 1
print_info: n_ctx_orig_yarn  = 131072
print_info: rope_finetuned   = unknown
print_info: ssm_d_conv       = 0
print_info: ssm_d_inner      = 0
print_info: ssm_d_state      = 0
print_info: ssm_dt_rank      = 0
print_info: ssm_dt_b_c_rms   = 0
print_info: model type       = 3B
print_info: model params     = 3.21 B
print_info: general.name     = Llama 3.2 3B Instruct
print_info: vocab type       = BPE
print_info: n_vocab          = 128256
print_info: n_merges         = 280147
print_info: BOS token        = 128000 '<|begin_of_text|>'
print_info: EOS token        = 128009 '<|eot_id|>'
print_info: EOT token        = 128009 '<|eot_id|>'
print_info: EOM token        = 128008 '<|eom_id|>'
print_info: LF token         = 198 'Ċ'
print_info: EOG token        = 128001 '<|end_of_text|>'
print_info: EOG token        = 128008 '<|eom_id|>'
print_info: EOG token        = 128009 '<|eot_id|>'
print_info: max token length = 256
load_tensors: loading model tensors, this can take a while... (mmap = true)
load_tensors: layer   0 assigned to device ROCm0, is_swa = 0
load_tensors: layer   1 assigned to device ROCm0, is_swa = 0
load_tensors: layer   2 assigned to device ROCm0, is_swa = 0
load_tensors: layer   3 assigned to device ROCm0, is_swa = 0
load_tensors: layer   4 assigned to device ROCm0, is_swa = 0
load_tensors: layer   5 assigned to device ROCm0, is_swa = 0
load_tensors: layer   6 assigned to device ROCm0, is_swa = 0
load_tensors: layer   7 assigned to device ROCm0, is_swa = 0
load_tensors: layer   8 assigned to device ROCm0, is_swa = 0
load_tensors: layer   9 assigned to device ROCm0, is_swa = 0
load_tensors: layer  10 assigned to device ROCm0, is_swa = 0
load_tensors: layer  11 assigned to device ROCm0, is_swa = 0
load_tensors: layer  12 assigned to device ROCm0, is_swa = 0
load_tensors: layer  13 assigned to device ROCm0, is_swa = 0
load_tensors: layer  14 assigned to device ROCm0, is_swa = 0
load_tensors: layer  15 assigned to device ROCm0, is_swa = 0
load_tensors: layer  16 assigned to device ROCm0, is_swa = 0
load_tensors: layer  17 assigned to device ROCm0, is_swa = 0
load_tensors: layer  18 assigned to device ROCm0, is_swa = 0
load_tensors: layer  19 assigned to device ROCm0, is_swa = 0
load_tensors: layer  20 assigned to device ROCm0, is_swa = 0
load_tensors: layer  21 assigned to device ROCm0, is_swa = 0
load_tensors: layer  22 assigned to device ROCm0, is_swa = 0
load_tensors: layer  23 assigned to device ROCm0, is_swa = 0
load_tensors: layer  24 assigned to device ROCm0, is_swa = 0
load_tensors: layer  25 assigned to device ROCm0, is_swa = 0
load_tensors: layer  26 assigned to device ROCm0, is_swa = 0
load_tensors: layer  27 assigned to device ROCm0, is_swa = 0
load_tensors: layer  28 assigned to device ROCm0, is_swa = 0
load_tensors: tensor 'token_embd.weight' (q6_K) (and 0 others) cannot be used with preferred buffer type ROCm_Host, using CPU instead
load_tensors: offloading 28 repeating layers to GPU
load_tensors: offloading output layer to GPU
load_tensors: offloaded 29/29 layers to GPU
load_tensors:   CPU_Mapped model buffer size =   308.23 MiB
load_tensors:        ROCm0 model buffer size =  1918.35 MiB
...........................................................................
llama_context: constructing llama_context
llama_context: n_seq_max     = 1
llama_context: n_ctx         = 2048
llama_context: n_ctx_per_seq = 2048
llama_context: n_batch       = 2048
llama_context: n_ubatch      = 512
llama_context: causal_attn   = 1
llama_context: flash_attn    = 0
llama_context: freq_base     = 500000.0
llama_context: freq_scale    = 1
llama_context: n_ctx_per_seq (2048) < n_ctx_train (131072) -- the full capacity of the model will not be utilized
set_abort_callback: call
llama_context:  ROCm_Host  output buffer size =     0.49 MiB
create_memory: n_ctx = 2048 (padded)
llama_kv_cache_unified: layer   0: dev = ROCm0
llama_kv_cache_unified: layer   1: dev = ROCm0
llama_kv_cache_unified: layer   2: dev = ROCm0
llama_kv_cache_unified: layer   3: dev = ROCm0
llama_kv_cache_unified: layer   4: dev = ROCm0
llama_kv_cache_unified: layer   5: dev = ROCm0
llama_kv_cache_unified: layer   6: dev = ROCm0
llama_kv_cache_unified: layer   7: dev = ROCm0
llama_kv_cache_unified: layer   8: dev = ROCm0
llama_kv_cache_unified: layer   9: dev = ROCm0
llama_kv_cache_unified: layer  10: dev = ROCm0
llama_kv_cache_unified: layer  11: dev = ROCm0
llama_kv_cache_unified: layer  12: dev = ROCm0
llama_kv_cache_unified: layer  13: dev = ROCm0
llama_kv_cache_unified: layer  14: dev = ROCm0
llama_kv_cache_unified: layer  15: dev = ROCm0
llama_kv_cache_unified: layer  16: dev = ROCm0
llama_kv_cache_unified: layer  17: dev = ROCm0
llama_kv_cache_unified: layer  18: dev = ROCm0
llama_kv_cache_unified: layer  19: dev = ROCm0
llama_kv_cache_unified: layer  20: dev = ROCm0
llama_kv_cache_unified: layer  21: dev = ROCm0
llama_kv_cache_unified: layer  22: dev = ROCm0
llama_kv_cache_unified: layer  23: dev = ROCm0
llama_kv_cache_unified: layer  24: dev = ROCm0
llama_kv_cache_unified: layer  25: dev = ROCm0
llama_kv_cache_unified: layer  26: dev = ROCm0
llama_kv_cache_unified: layer  27: dev = ROCm0
llama_kv_cache_unified:      ROCm0 KV buffer size =   224.00 MiB
llama_kv_cache_unified: size =  224.00 MiB (  2048 cells,  28 layers,  1 seqs), K (f16):  112.00 MiB, V (f16):  112.00 MiB
llama_context: enumerating backends
llama_context: backend_ptrs.size() = 2
llama_context: max_nodes = 65536
llama_context: worst-case: n_tokens = 512, n_seqs = 1, n_outputs = 0
graph_reserve: reserving a graph for ubatch with n_tokens =  512, n_seqs =  1, n_outputs =  512
graph_reserve: reserving a graph for ubatch with n_tokens =    1, n_seqs =  1, n_outputs =    1
graph_reserve: reserving a graph for ubatch with n_tokens =  512, n_seqs =  1, n_outputs =  512
llama_context:      ROCm0 compute buffer size =   256.50 MiB
llama_context:  ROCm_Host compute buffer size =    10.01 MiB
llama_context: graph nodes  = 1014
llama_context: graph splits = 2
clear_adapter_lora: call
common_init_from_params: setting dry_penalty_last_n to ctx_size = 2048
srv          init: initializing slots, n_slots = 1
slot         init: id  0 | task -1 | new slot n_ctx_slot = 2048
slot        reset: id  0 | task -1 | 
main: model loaded
main: chat template, chat_template: {{- bos_token }}
{%- if custom_tools is defined %}
    {%- set tools = custom_tools %}
{%- endif %}
{%- if not tools_in_user_message is defined %}
    {%- set tools_in_user_message = true %}
{%- endif %}
{%- if not date_string is defined %}
    {%- if strftime_now is defined %}
        {%- set date_string = strftime_now("%d %b %Y") %}
    {%- else %}
        {%- set date_string = "26 Jul 2024" %}
    {%- endif %}
{%- endif %}
{%- if not tools is defined %}
    {%- set tools = none %}
{%- endif %}

{#- This block extracts the system message, so we can slot it into the right place. #}
{%- if messages[0]['role'] == 'system' %}
    {%- set system_message = messages[0]['content']|trim %}
    {%- set messages = messages[1:] %}
{%- else %}
    {%- set system_message = "" %}
{%- endif %}

{#- System message #}
{{- "<|start_header_id|>system<|end_header_id|>\n\n" }}
{%- if tools is not none %}
    {{- "Environment: ipython\n" }}
{%- endif %}
{{- "Cutting Knowledge Date: December 2023\n" }}
{{- "Today Date: " + date_string + "\n\n" }}
{%- if tools is not none and not tools_in_user_message %}
    {{- "You have access to the following functions. To call a function, please respond with JSON for a function call." }}
    {{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
    {{- "Do not use variables.\n\n" }}
    {%- for t in tools %}
        {{- t | tojson(indent=4) }}
        {{- "\n\n" }}
    {%- endfor %}
{%- endif %}
{{- system_message }}
{{- "<|eot_id|>" }}

{#- Custom tools are passed in a user message with some extra guidance #}
{%- if tools_in_user_message and not tools is none %}
    {#- Extract the first user message so we can plug it in here #}
    {%- if messages | length != 0 %}
        {%- set first_user_message = messages[0]['content']|trim %}
        {%- set messages = messages[1:] %}
    {%- else %}
        {{- raise_exception("Cannot put tools in the first user message when there's no first user message!") }}
{%- endif %}
    {{- '<|start_header_id|>user<|end_header_id|>\n\n' -}}
    {{- "Given the following functions, please respond with a JSON for a function call " }}
    {{- "with its proper arguments that best answers the given prompt.\n\n" }}
    {{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
    {{- "Do not use variables.\n\n" }}
    {%- for t in tools %}
        {{- t | tojson(indent=4) }}
        {{- "\n\n" }}
    {%- endfor %}
    {{- first_user_message + "<|eot_id|>"}}
{%- endif %}

{%- for message in messages %}
    {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}
        {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' }}
    {%- elif 'tool_calls' in message %}
        {%- if not message.tool_calls|length == 1 %}
            {{- raise_exception("This model only supports single tool-calls at once!") }}
        {%- endif %}
        {%- set tool_call = message.tool_calls[0].function %}
        {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
        {{- '{"name": "' + tool_call.name + '", ' }}
        {{- '"parameters": ' }}
        {{- tool_call.arguments | tojson }}
        {{- "}" }}
        {{- "<|eot_id|>" }}
    {%- elif message.role == "tool" or message.role == "ipython" %}
        {{- "<|start_header_id|>ipython<|end_header_id|>\n\n" }}
        {%- if message.content is mapping or message.content is iterable %}
            {{- message.content | tojson }}
        {%- else %}
            {{- message.content }}
        {%- endif %}
        {{- "<|eot_id|>" }}
    {%- endif %}
{%- endfor %}
{%- if add_generation_prompt %}docker run --rm --label ai.ramalama.model=llama3.2:3b --label ai.ramalama.engine=docker --label ai.ramalama.runtime=llama.cpp --label ai.ramalama.port=8080 --label ai.ramalama.command=run --device /dev/dri --device /dev/kfd -e HIP_VISIBLE_DEVICES=1 -p 8080:8080 --security-opt=label=disable --cap-drop=all --security-opt=no-new-privileges -t -i --label ai.ramalama --name ramalama_IGngq1HF2u --env=HOME=/tmp --init --mount=type=bind,src=/home/mypc/.local/share/ramalama/store/ollama/library/llama3.2/blobs/sha256-dde5aa3fc5ffc17176b5e8bdc82f587b24b2678c6c66101bf7da77af9f7ccdff,destination=/mnt/models/llama3.2,ro --mount=type=bind,src=/home/mypc/.local/share/ramalama/store/ollama/library/llama3.2/blobs/sha256-34bb5ab01051a11372a91f95f3fbbc51173eed8e7f13ec395b9ae9b8bd0e242b,destination=/mnt/models/config.json,ro --mount=type=bind,src=/home/mypc/.local/share/ramalama/store/ollama/library/llama3.2/blobs/sha256-966de95ca8a62200913e3f8bfbf84c8494536f1b94b49166851e76644e966396,destination=/mnt/models/chat_template,ro quay.io/ramalama/rocm:latest llama-server --port 8080 --model /mnt/models/llama3.2 --no-warmup --jinja --log-colors --alias llama3.2:3b --ctx-size 2048 --temp 0.8 --cache-reuse 256 -v -ngl 999 --threads 12 --host 0.0.0.0 

ggml_cuda_init: GGML_CUDA_FORCE_MMQ:    no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 1 ROCm devices:
  Device 0: AMD Radeon Graphics, gfx1036 (0x1036), VMM: no, Wave Size: 32
build: 5764 (f667f1e6) with cc (GCC) 15.1.1 20250521 (Red Hat 15.1.1-2) for x86_64-redhat-linux
system info: n_threads = 12, n_threads_batch = 12, total_threads = 24

system_info: n_threads = 12 (n_threads_batch = 12) / 24 | ROCm : NO_VMM = 1 | PEER_MAX_BATCH_SIZE = 128 | CPU : SSE3 = 1 | SSSE3 = 1 | AVX = 1 | AVX2 = 1 | F16C = 1 | FMA = 1 | BMI2 = 1 | LLAMAFILE = 1 | OPENMP = 1 | REPACK = 1 | 

main: binding port with default address family
main: HTTP server is listening, hostname: 0.0.0.0, port: 8080, http threads: 23
main: loading model
srv    load_model: loading model '/mnt/models/llama3.2'
llama_model_load_from_file_impl: using device ROCm0 (AMD Radeon Graphics) - 31668 MiB free
llama_model_loader: loaded meta data with 30 key-value pairs and 255 tensors from /mnt/models/llama3.2 (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv   0:                       general.architecture str              = llama
llama_model_loader: - kv   1:                               general.type str              = model
llama_model_loader: - kv   2:                               general.name str              = Llama 3.2 3B Instruct
llama_model_loader: - kv   3:                           general.finetune str              = Instruct
llama_model_loader: - kv   4:                           general.basename str              = Llama-3.2
llama_model_loader: - kv   5:                         general.size_label str              = 3B
llama_model_loader: - kv   6:                               general.tags arr[str,6]       = ["facebook", "meta", "pytorch", "llam...
llama_model_loader: - kv   7:                          general.languages arr[str,8]       = ["en", "de", "fr", "it", "pt", "hi", ...
llama_model_loader: - kv   8:                          llama.block_count u32              = 28
llama_model_loader: - kv   9:                       llama.context_length u32              = 131072
llama_model_loader: - kv  10:                     llama.embedding_length u32              = 3072
llama_model_loader: - kv  11:                  llama.feed_forward_length u32              = 8192
llama_model_loader: - kv  12:                 llama.attention.head_count u32              = 24
llama_model_loader: - kv  13:              llama.attention.head_count_kv u32              = 8
llama_model_loader: - kv  14:                       llama.rope.freq_base f32              = 500000.000000
llama_model_loader: - kv  15:     llama.attention.layer_norm_rms_epsilon f32              = 0.000010
llama_model_loader: - kv  16:                 llama.attention.key_length u32              = 128
llama_model_loader: - kv  17:               llama.attention.value_length u32              = 128
llama_model_loader: - kv  18:                          general.file_type u32              = 15
llama_model_loader: - kv  19:                           llama.vocab_size u32              = 128256
llama_model_loader: - kv  20:                 llama.rope.dimension_count u32              = 128
llama_model_loader: - kv  21:                       tokenizer.ggml.model str              = gpt2
llama_model_loader: - kv  22:                         tokenizer.ggml.pre str              = llama-bpe
llama_model_loader: - kv  23:                      tokenizer.ggml.tokens arr[str,128256]  = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv  24:                  tokenizer.ggml.token_type arr[i32,128256]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv  25:                      tokenizer.ggml.merges arr[str,280147]  = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "...
llama_model_loader: - kv  26:                tokenizer.ggml.bos_token_id u32              = 128000
llama_model_loader: - kv  27:                tokenizer.ggml.eos_token_id u32              = 128009
llama_model_loader: - kv  28:                    tokenizer.chat_template str              = {{- bos_token }}\n{%- if custom_tools ...
llama_model_loader: - kv  29:               general.quantization_version u32              = 2
llama_model_loader: - type  f32:   58 tensors
llama_model_loader: - type q4_K:  168 tensors
llama_model_loader: - type q6_K:   29 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type   = Q4_K - Medium
print_info: file size   = 1.87 GiB (5.01 BPW) 
init_tokenizer: initializing tokenizer for type 2
load: control token: 128254 '<|reserved_special_token_246|>' is not marked as EOG
load: control token: 128249 '<|reserved_special_token_241|>' is not marked as EOG
load: control token: 128246 '<|reserved_special_token_238|>' is not marked as EOG
load: control token: 128243 '<|reserved_special_token_235|>' is not marked as EOG
load: control token: 128242 '<|reserved_special_token_234|>' is not marked as EOG
load: control token: 128241 '<|reserved_special_token_233|>' is not marked as EOG
load: control token: 128240 '<|reserved_special_token_232|>' is not marked as EOG
load: control token: 128235 '<|reserved_special_token_227|>' is not marked as EOG
load: control token: 128231 '<|reserved_special_token_223|>' is not marked as EOG
load: control token: 128230 '<|reserved_special_token_222|>' is not marked as EOG
load: control token: 128228 '<|reserved_special_token_220|>' is not marked as EOG
load: control token: 128225 '<|reserved_special_token_217|>' is not marked as EOG
load: control token: 128218 '<|reserved_special_token_210|>' is not marked as EOG
load: control token: 128214 '<|reserved_special_token_206|>' is not marked as EOG
load: control token: 128213 '<|reserved_special_token_205|>' is not marked as EOG
load: control token: 128207 '<|reserved_special_token_199|>' is not marked as EOG
load: control token: 128206 '<|reserved_special_token_198|>' is not marked as EOG
load: control token: 128204 '<|reserved_special_token_196|>' is not marked as EOG
load: control token: 128200 '<|reserved_special_token_192|>' is not marked as EOG
load: control token: 128199 '<|reserved_special_token_191|>' is not marked as EOG
load: control token: 128198 '<|reserved_special_token_190|>' is not marked as EOG
load: control token: 128196 '<|reserved_special_token_188|>' is not marked as EOG
load: control token: 128194 '<|reserved_special_token_186|>' is not marked as EOG
load: control token: 128193 '<|reserved_special_token_185|>' is not marked as EOG
load: control token: 128188 '<|reserved_special_token_180|>' is not marked as EOG
load: control token: 128187 '<|reserved_special_token_179|>' is not marked as EOG
load: control token: 128185 '<|reserved_special_token_177|>' is not marked as EOG
load: control token: 128184 '<|reserved_special_token_176|>' is not marked as EOG
load: control token: 128180 '<|reserved_special_token_172|>' is not marked as EOG
load: control token: 128179 '<|reserved_special_token_171|>' is not marked as EOG
load: control token: 128178 '<|reserved_special_token_170|>' is not marked as EOG
load: control token: 128177 '<|reserved_special_token_169|>' is not marked as EOG
load: control token: 128176 '<|reserved_special_token_168|>' is not marked as EOG
load: control token: 128175 '<|reserved_special_token_167|>' is not marked as EOG
load: control token: 128171 '<|reserved_special_token_163|>' is not marked as EOG
load: control token: 128170 '<|reserved_special_token_162|>' is not marked as EOG
load: control token: 128169 '<|reserved_special_token_161|>' is not marked as EOG
load: control token: 128168 '<|reserved_special_token_160|>' is not marked as EOG
load: control token: 128165 '<|reserved_special_token_157|>' is not marked as EOG
load: control token: 128162 '<|reserved_special_token_154|>' is not marked as EOG
load: control token: 128158 '<|reserved_special_token_150|>' is not marked as EOG
load: control token: 128156 '<|reserved_special_token_148|>' is not marked as EOG
load: control token: 128155 '<|reserved_special_token_147|>' is not marked as EOG
load: control token: 128154 '<|reserved_special_token_146|>' is not marked as EOG
load: control token: 128151 '<|reserved_special_token_143|>' is not marked as EOG
load: control token: 128149 '<|reserved_special_token_141|>' is not marked as EOG
load: control token: 128147 '<|reserved_special_token_139|>' is not marked as EOG
load: control token: 128146 '<|reserved_special_token_138|>' is not marked as EOG
load: control token: 128144 '<|reserved_special_token_136|>' is not marked as EOG
load: control token: 128142 '<|reserved_special_token_134|>' is not marked as EOG
load: control token: 128141 '<|reserved_special_token_133|>' is not marked as EOG
load: control token: 128138 '<|reserved_special_token_130|>' is not marked as EOG
load: control token: 128136 '<|reserved_special_token_128|>' is not marked as EOG
load: control token: 128135 '<|reserved_special_token_127|>' is not marked as EOG
load: control token: 128134 '<|reserved_special_token_126|>' is not marked as EOG
load: control token: 128133 '<|reserved_special_token_125|>' is not marked as EOG
load: control token: 128131 '<|reserved_special_token_123|>' is not marked as EOG
load: control token: 128128 '<|reserved_special_token_120|>' is not marked as EOG
load: control token: 128124 '<|reserved_special_token_116|>' is not marked as EOG
load: control token: 128123 '<|reserved_special_token_115|>' is not marked as EOG
load: control token: 128122 '<|reserved_special_token_114|>' is not marked as EOG
load: control token: 128119 '<|reserved_special_token_111|>' is not marked as EOG
load: control token: 128115 '<|reserved_special_token_107|>' is not marked as EOG
load: control token: 128112 '<|reserved_special_token_104|>' is not marked as EOG
load: control token: 128110 '<|reserved_special_token_102|>' is not marked as EOG
load: control token: 128109 '<|reserved_special_token_101|>' is not marked as EOG
load: control token: 128108 '<|reserved_special_token_100|>' is not marked as EOG
load: control token: 128106 '<|reserved_special_token_98|>' is not marked as EOG
load: control token: 128103 '<|reserved_special_token_95|>' is not marked as EOG
load: control token: 128102 '<|reserved_special_token_94|>' is not marked as EOG
load: control token: 128101 '<|reserved_special_token_93|>' is not marked as EOG
load: control token: 128097 '<|reserved_special_token_89|>' is not marked as EOG
load: control token: 128091 '<|reserved_special_token_83|>' is not marked as EOG
load: control token: 128090 '<|reserved_special_token_82|>' is not marked as EOG
load: control token: 128089 '<|reserved_special_token_81|>' is not marked as EOG
load: control token: 128087 '<|reserved_special_token_79|>' is not marked as EOG
load: control token: 128085 '<|reserved_special_token_77|>' is not marked as EOG
load: control token: 128081 '<|reserved_special_token_73|>' is not marked as EOG
load: control token: 128078 '<|reserved_special_token_70|>' is not marked as EOG
load: control token: 128076 '<|reserved_special_token_68|>' is not marked as EOG
load: control token: 128075 '<|reserved_special_token_67|>' is not marked as EOG
load: control token: 128073 '<|reserved_special_token_65|>' is not marked as EOG
load: control token: 128068 '<|reserved_special_token_60|>' is not marked as EOG
load: control token: 128067 '<|reserved_special_token_59|>' is not marked as EOG
load: control token: 128065 '<|reserved_special_token_57|>' is not marked as EOG
load: control token: 128063 '<|reserved_special_token_55|>' is not marked as EOG
load: control token: 128062 '<|reserved_special_token_54|>' is not marked as EOG
load: control token: 128060 '<|reserved_special_token_52|>' is not marked as EOG
load: control token: 128059 '<|reserved_special_token_51|>' is not marked as EOG
load: control token: 128057 '<|reserved_special_token_49|>' is not marked as EOG
load: control token: 128054 '<|reserved_special_token_46|>' is not marked as EOG
load: control token: 128046 '<|reserved_special_token_38|>' is not marked as EOG
load: control token: 128045 '<|reserved_special_token_37|>' is not marked as EOG
load: control token: 128044 '<|reserved_special_token_36|>' is not marked as EOG
load: control token: 128043 '<|reserved_special_token_35|>' is not marked as EOG
load: control token: 128038 '<|reserved_special_token_30|>' is not marked as EOG
load: control token: 128036 '<|reserved_special_token_28|>' is not marked as EOG
load: control token: 128035 '<|reserved_special_token_27|>' is not marked as EOG
load: control token: 128032 '<|reserved_special_token_24|>' is not marked as EOG
load: control token: 128028 '<|reserved_special_token_20|>' is not marked as EOG
load: control token: 128027 '<|reserved_special_token_19|>' is not marked as EOG
load: control token: 128024 '<|reserved_special_token_16|>' is not marked as EOG
load: control token: 128023 '<|reserved_special_token_15|>' is not marked as EOG
load: control token: 128022 '<|reserved_special_token_14|>' is not marked as EOG
load: control token: 128021 '<|reserved_special_token_13|>' is not marked as EOG
load: control token: 128018 '<|reserved_special_token_10|>' is not marked as EOG
load: control token: 128016 '<|reserved_special_token_8|>' is not marked as EOG
load: control token: 128015 '<|reserved_special_token_7|>' is not marked as EOG
load: control token: 128013 '<|reserved_special_token_5|>' is not marked as EOG
load: control token: 128011 '<|reserved_special_token_3|>' is not marked as EOG
load: control token: 128005 '<|reserved_special_token_2|>' is not marked as EOG
load: control token: 128004 '<|finetune_right_pad_id|>' is not marked as EOG
load: control token: 128002 '<|reserved_special_token_0|>' is not marked as EOG
load: control token: 128252 '<|reserved_special_token_244|>' is not marked as EOG
load: control token: 128190 '<|reserved_special_token_182|>' is not marked as EOG
load: control token: 128183 '<|reserved_special_token_175|>' is not marked as EOG
load: control token: 128137 '<|reserved_special_token_129|>' is not marked as EOG
load: control token: 128182 '<|reserved_special_token_174|>' is not marked as EOG
load: control token: 128040 '<|reserved_special_token_32|>' is not marked as EOG
load: control token: 128048 '<|reserved_special_token_40|>' is not marked as EOG
load: control token: 128092 '<|reserved_special_token_84|>' is not marked as EOG
load: control token: 128215 '<|reserved_special_token_207|>' is not marked as EOG
load: control token: 128107 '<|reserved_special_token_99|>' is not marked as EOG
load: control token: 128208 '<|reserved_special_token_200|>' is not marked as EOG
load: control token: 128145 '<|reserved_special_token_137|>' is not marked as EOG
load: control token: 128031 '<|reserved_special_token_23|>' is not marked as EOG
load: control token: 128129 '<|reserved_special_token_121|>' is not marked as EOG
load: control token: 128201 '<|reserved_special_token_193|>' is not marked as EOG
load: control token: 128074 '<|reserved_special_token_66|>' is not marked as EOG
load: control token: 128095 '<|reserved_special_token_87|>' is not marked as EOG
load: control token: 128186 '<|reserved_special_token_178|>' is not marked as EOG
load: control token: 128143 '<|reserved_special_token_135|>' is not marked as EOG
load: control token: 128229 '<|reserved_special_token_221|>' is not marked as EOG
load: control token: 128007 '<|end_header_id|>' is not marked as EOG
load: control token: 128055 '<|reserved_special_token_47|>' is not marked as EOG
load: control token: 128056 '<|reserved_special_token_48|>' is not marked as EOG
load: control token: 128061 '<|reserved_special_token_53|>' is not marked as EOG
load: control token: 128153 '<|reserved_special_token_145|>' is not marked as EOG
load: control token: 128152 '<|reserved_special_token_144|>' is not marked as EOG
load: control token: 128212 '<|reserved_special_token_204|>' is not marked as EOG
load: control token: 128172 '<|reserved_special_token_164|>' is not marked as EOG
load: control token: 128160 '<|reserved_special_token_152|>' is not marked as EOG
load: control token: 128041 '<|reserved_special_token_33|>' is not marked as EOG
load: control token: 128181 '<|reserved_special_token_173|>' is not marked as EOG
load: control token: 128094 '<|reserved_special_token_86|>' is not marked as EOG
load: control token: 128118 '<|reserved_special_token_110|>' is not marked as EOG
load: control token: 128236 '<|reserved_special_token_228|>' is not marked as EOG
load: control token: 128148 '<|reserved_special_token_140|>' is not marked as EOG
load: control token: 128042 '<|reserved_special_token_34|>' is not marked as EOG
load: control token: 128139 '<|reserved_special_token_131|>' is not marked as EOG
load: control token: 128173 '<|reserved_special_token_165|>' is not marked as EOG
load: control token: 128239 '<|reserved_special_token_231|>' is not marked as EOG
load: control token: 128157 '<|reserved_special_token_149|>' is not marked as EOG
load: control token: 128052 '<|reserved_special_token_44|>' is not marked as EOG
load: control token: 128026 '<|reserved_special_token_18|>' is not marked as EOG
load: control token: 128003 '<|reserved_special_token_1|>' is not marked as EOG
load: control token: 128019 '<|reserved_special_token_11|>' is not marked as EOG
load: control token: 128116 '<|reserved_special_token_108|>' is not marked as EOG
load: control token: 128161 '<|reserved_special_token_153|>' is not marked as EOG
load: control token: 128226 '<|reserved_special_token_218|>' is not marked as EOG
load: control token: 128159 '<|reserved_special_token_151|>' is not marked as EOG
load: control token: 128012 '<|reserved_special_token_4|>' is not marked as EOG
load: control token: 128088 '<|reserved_special_token_80|>' is not marked as EOG
load: control token: 128163 '<|reserved_special_token_155|>' is not marked as EOG
load: control token: 128113 '<|reserved_special_token_105|>' is not marked as EOG
load: control token: 128250 '<|reserved_special_token_242|>' is not marked as EOG
load: control token: 128125 '<|reserved_special_token_117|>' is not marked as EOG
load: control token: 128053 '<|reserved_special_token_45|>' is not marked as EOG
load: control token: 128224 '<|reserved_special_token_216|>' is not marked as EOG
load: control token: 128247 '<|reserved_special_token_239|>' is not marked as EOG
load: control token: 128251 '<|reserved_special_token_243|>' is not marked as EOG
load: control token: 128216 '<|reserved_special_token_208|>' is not marked as EOG
load: control token: 128006 '<|start_header_id|>' is not marked as EOG
load: control token: 128211 '<|reserved_special_token_203|>' is not marked as EOG
load: control token: 128077 '<|reserved_special_token_69|>' is not marked as EOG
load: control token: 128237 '<|reserved_special_token_229|>' is not marked as EOG
load: control token: 128086 '<|reserved_special_token_78|>' is not marked as EOG
load: control token: 128227 '<|reserved_special_token_219|>' is not marked as EOG
load: control token: 128058 '<|reserved_special_token_50|>' is not marked as EOG
load: control token: 128100 '<|reserved_special_token_92|>' is not marked as EOG
load: control token: 128209 '<|reserved_special_token_201|>' is not marked as EOG
load: control token: 128084 '<|reserved_special_token_76|>' is not marked as EOG
load: control token: 128071 '<|reserved_special_token_63|>' is not marked as EOG
load: control token: 128070 '<|reserved_special_token_62|>' is not marked as EOG
load: control token: 128049 '<|reserved_special_token_41|>' is not marked as EOG
load: control token: 128197 '<|reserved_special_token_189|>' is not marked as EOG
load: control token: 128072 '<|reserved_special_token_64|>' is not marked as EOG
load: control token: 128000 '<|begin_of_text|>' is not marked as EOG
load: control token: 128223 '<|reserved_special_token_215|>' is not marked as EOG
load: control token: 128217 '<|reserved_special_token_209|>' is not marked as EOG
load: control token: 128111 '<|reserved_special_token_103|>' is not marked as EOG
load: control token: 128203 '<|reserved_special_token_195|>' is not marked as EOG
load: control token: 128051 '<|reserved_special_token_43|>' is not marked as EOG
load: control token: 128030 '<|reserved_special_token_22|>' is not marked as EOG
load: control token: 128117 '<|reserved_special_token_109|>' is not marked as EOG
load: control token: 128010 '<|python_tag|>' is not marked as EOG
load: control token: 128238 '<|reserved_special_token_230|>' is not marked as EOG
load: control token: 128255 '<|reserved_special_token_247|>' is not marked as EOG
load: control token: 128202 '<|reserved_special_token_194|>' is not marked as EOG
load: control token: 128132 '<|reserved_special_token_124|>' is not marked as EOG
load: control token: 128248 '<|reserved_special_token_240|>' is not marked as EOG
load: control token: 128167 '<|reserved_special_token_159|>' is not marked as EOG
load: control token: 128127 '<|reserved_special_token_119|>' is not marked as EOG
load: control token: 128105 '<|reserved_special_token_97|>' is not marked as EOG
load: control token: 128039 '<|reserved_special_token_31|>' is not marked as EOG
load: control token: 128232 '<|reserved_special_token_224|>' is not marked as EOG
load: control token: 128166 '<|reserved_special_token_158|>' is not marked as EOG
load: control token: 128130 '<|reserved_special_token_122|>' is not marked as EOG
load: control token: 128114 '<|reserved_special_token_106|>' is not marked as EOG
load: control token: 128234 '<|reserved_special_token_226|>' is not marked as EOG
load: control token: 128191 '<|reserved_special_token_183|>' is not marked as EOG
load: control token: 128064 '<|reserved_special_token_56|>' is not marked as EOG
load: control token: 128140 '<|reserved_special_token_132|>' is not marked as EOG
load: control token: 128096 '<|reserved_special_token_88|>' is not marked as EOG
load: control token: 128098 '<|reserved_special_token_90|>' is not marked as EOG
load: control token: 128192 '<|reserved_special_token_184|>' is not marked as EOG
load: control token: 128093 '<|reserved_special_token_85|>' is not marked as EOG
load: control token: 128150 '<|reserved_special_token_142|>' is not marked as EOG
load: control token: 128222 '<|reserved_special_token_214|>' is not marked as EOG
load: control token: 128233 '<|reserved_special_token_225|>' is not marked as EOG
load: control token: 128220 '<|reserved_special_token_212|>' is not marked as EOG
load: control token: 128034 '<|reserved_special_token_26|>' is not marked as EOG
load: control token: 128033 '<|reserved_special_token_25|>' is not marked as EOG
load: control token: 128253 '<|reserved_special_token_245|>' is not marked as EOG
load: control token: 128195 '<|reserved_special_token_187|>' is not marked as EOG
load: control token: 128099 '<|reserved_special_token_91|>' is not marked as EOG
load: control token: 128189 '<|reserved_special_token_181|>' is not marked as EOG
load: control token: 128210 '<|reserved_special_token_202|>' is not marked as EOG
load: control token: 128174 '<|reserved_special_token_166|>' is not marked as EOG
load: control token: 128083 '<|reserved_special_token_75|>' is not marked as EOG
load: control token: 128080 '<|reserved_special_token_72|>' is not marked as EOG
load: control token: 128104 '<|reserved_special_token_96|>' is not marked as EOG
load: control token: 128082 '<|reserved_special_token_74|>' is not marked as EOG
load: control token: 128219 '<|reserved_special_token_211|>' is not marked as EOG
load: control token: 128017 '<|reserved_special_token_9|>' is not marked as EOG
load: control token: 128050 '<|reserved_special_token_42|>' is not marked as EOG
load: control token: 128205 '<|reserved_special_token_197|>' is not marked as EOG
load: control token: 128047 '<|reserved_special_token_39|>' is not marked as EOG
load: control token: 128164 '<|reserved_special_token_156|>' is not marked as EOG
load: control token: 128020 '<|reserved_special_token_12|>' is not marked as EOG
load: control token: 128069 '<|reserved_special_token_61|>' is not marked as EOG
load: control token: 128245 '<|reserved_special_token_237|>' is not marked as EOG
load: control token: 128121 '<|reserved_special_token_113|>' is not marked as EOG
load: control token: 128079 '<|reserved_special_token_71|>' is not marked as EOG
load: control token: 128037 '<|reserved_special_token_29|>' is not marked as EOG
load: control token: 128244 '<|reserved_special_token_236|>' is not marked as EOG
load: control token: 128029 '<|reserved_special_token_21|>' is not marked as EOG
load: control token: 128221 '<|reserved_special_token_213|>' is not marked as EOG
load: control token: 128066 '<|reserved_special_token_58|>' is not marked as EOG
load: control token: 128120 '<|reserved_special_token_112|>' is not marked as EOG
load: control token: 128014 '<|reserved_special_token_6|>' is not marked as EOG
load: control token: 128025 '<|reserved_special_token_17|>' is not marked as EOG
load: control token: 128126 '<|reserved_special_token_118|>' is not marked as EOG
load: special tokens cache size = 256
load: token to piece cache size = 0.7999 MB
print_info: arch             = llama
print_info: vocab_only       = 0
print_info: n_ctx_train      = 131072
print_info: n_embd           = 3072
print_info: n_layer          = 28
print_info: n_head           = 24
print_info: n_head_kv        = 8
print_info: n_rot            = 128
print_info: n_swa            = 0
print_info: is_swa_any       = 0
print_info: n_embd_head_k    = 128
print_info: n_embd_head_v    = 128
print_info: n_gqa            = 3
print_info: n_embd_k_gqa     = 1024
print_info: n_embd_v_gqa     = 1024
print_info: f_norm_eps       = 0.0e+00
print_info: f_norm_rms_eps   = 1.0e-05
print_info: f_clamp_kqv      = 0.0e+00
print_info: f_max_alibi_bias = 0.0e+00
print_info: f_logit_scale    = 0.0e+00
print_info: f_attn_scale     = 0.0e+00
print_info: n_ff             = 8192
print_info: n_expert         = 0
print_info: n_expert_used    = 0
print_info: causal attn      = 1
print_info: pooling type     = 0
print_info: rope type        = 0
print_info: rope scaling     = linear
print_info: freq_base_train  = 500000.0
print_info: freq_scale_train = 1
print_info: n_ctx_orig_yarn  = 131072
print_info: rope_finetuned   = unknown
print_info: ssm_d_conv       = 0
print_info: ssm_d_inner      = 0
print_info: ssm_d_state      = 0
print_info: ssm_dt_rank      = 0
print_info: ssm_dt_b_c_rms   = 0
print_info: model type       = 3B
print_info: model params     = 3.21 B
print_info: general.name     = Llama 3.2 3B Instruct
print_info: vocab type       = BPE
print_info: n_vocab          = 128256
print_info: n_merges         = 280147
print_info: BOS token        = 128000 '<|begin_of_text|>'
print_info: EOS token        = 128009 '<|eot_id|>'
print_info: EOT token        = 128009 '<|eot_id|>'
print_info: EOM token        = 128008 '<|eom_id|>'
print_info: LF token         = 198 'Ċ'
print_info: EOG token        = 128001 '<|end_of_text|>'
print_info: EOG token        = 128008 '<|eom_id|>'
print_info: EOG token        = 128009 '<|eot_id|>'
print_info: max token length = 256
load_tensors: loading model tensors, this can take a while... (mmap = true)
load_tensors: layer   0 assigned to device ROCm0, is_swa = 0
load_tensors: layer   1 assigned to device ROCm0, is_swa = 0
load_tensors: layer   2 assigned to device ROCm0, is_swa = 0
load_tensors: layer   3 assigned to device ROCm0, is_swa = 0
load_tensors: layer   4 assigned to device ROCm0, is_swa = 0
load_tensors: layer   5 assigned to device ROCm0, is_swa = 0
load_tensors: layer   6 assigned to device ROCm0, is_swa = 0
load_tensors: layer   7 assigned to device ROCm0, is_swa = 0
load_tensors: layer   8 assigned to device ROCm0, is_swa = 0
load_tensors: layer   9 assigned to device ROCm0, is_swa = 0
load_tensors: layer  10 assigned to device ROCm0, is_swa = 0
load_tensors: layer  11 assigned to device ROCm0, is_swa = 0
load_tensors: layer  12 assigned to device ROCm0, is_swa = 0
load_tensors: layer  13 assigned to device ROCm0, is_swa = 0
load_tensors: layer  14 assigned to device ROCm0, is_swa = 0
load_tensors: layer  15 assigned to device ROCm0, is_swa = 0
load_tensors: layer  16 assigned to device ROCm0, is_swa = 0
load_tensors: layer  17 assigned to device ROCm0, is_swa = 0
load_tensors: layer  18 assigned to device ROCm0, is_swa = 0
load_tensors: layer  19 assigned to device ROCm0, is_swa = 0
load_tensors: layer  20 assigned to device ROCm0, is_swa = 0
load_tensors: layer  21 assigned to device ROCm0, is_swa = 0
load_tensors: layer  22 assigned to device ROCm0, is_swa = 0
load_tensors: layer  23 assigned to device ROCm0, is_swa = 0
load_tensors: layer  24 assigned to device ROCm0, is_swa = 0
load_tensors: layer  25 assigned to device ROCm0, is_swa = 0
load_tensors: layer  26 assigned to device ROCm0, is_swa = 0
load_tensors: layer  27 assigned to device ROCm0, is_swa = 0
load_tensors: layer  28 assigned to device ROCm0, is_swa = 0
load_tensors: tensor 'token_embd.weight' (q6_K) (and 0 others) cannot be used with preferred buffer type ROCm_Host, using CPU instead
load_tensors: offloading 28 repeating layers to GPU
load_tensors: offloading output layer to GPU
load_tensors: offloaded 29/29 layers to GPU
load_tensors:   CPU_Mapped model buffer size =   308.23 MiB
load_tensors:        ROCm0 model buffer size =  1918.35 MiB
...........................................................................
llama_context: constructing llama_context
llama_context: n_seq_max     = 1
llama_context: n_ctx         = 2048
llama_context: n_ctx_per_seq = 2048
llama_context: n_batch       = 2048
llama_context: n_ubatch      = 512
llama_context: causal_attn   = 1
llama_context: flash_attn    = 0
llama_context: freq_base     = 500000.0
llama_context: freq_scale    = 1
llama_context: n_ctx_per_seq (2048) < n_ctx_train (131072) -- the full capacity of the model will not be utilized
set_abort_callback: call
llama_context:  ROCm_Host  output buffer size =     0.49 MiB
create_memory: n_ctx = 2048 (padded)
llama_kv_cache_unified: layer   0: dev = ROCm0
llama_kv_cache_unified: layer   1: dev = ROCm0
llama_kv_cache_unified: layer   2: dev = ROCm0
llama_kv_cache_unified: layer   3: dev = ROCm0
llama_kv_cache_unified: layer   4: dev = ROCm0
llama_kv_cache_unified: layer   5: dev = ROCm0
llama_kv_cache_unified: layer   6: dev = ROCm0
llama_kv_cache_unified: layer   7: dev = ROCm0
llama_kv_cache_unified: layer   8: dev = ROCm0
llama_kv_cache_unified: layer   9: dev = ROCm0
llama_kv_cache_unified: layer  10: dev = ROCm0
llama_kv_cache_unified: layer  11: dev = ROCm0
llama_kv_cache_unified: layer  12: dev = ROCm0
llama_kv_cache_unified: layer  13: dev = ROCm0
llama_kv_cache_unified: layer  14: dev = ROCm0
llama_kv_cache_unified: layer  15: dev = ROCm0
llama_kv_cache_unified: layer  16: dev = ROCm0
llama_kv_cache_unified: layer  17: dev = ROCm0
llama_kv_cache_unified: layer  18: dev = ROCm0
llama_kv_cache_unified: layer  19: dev = ROCm0
llama_kv_cache_unified: layer  20: dev = ROCm0
llama_kv_cache_unified: layer  21: dev = ROCm0
llama_kv_cache_unified: layer  22: dev = ROCm0
llama_kv_cache_unified: layer  23: dev = ROCm0
llama_kv_cache_unified: layer  24: dev = ROCm0
llama_kv_cache_unified: layer  25: dev = ROCm0
llama_kv_cache_unified: layer  26: dev = ROCm0
llama_kv_cache_unified: layer  27: dev = ROCm0
llama_kv_cache_unified:      ROCm0 KV buffer size =   224.00 MiB
llama_kv_cache_unified: size =  224.00 MiB (  2048 cells,  28 layers,  1 seqs), K (f16):  112.00 MiB, V (f16):  112.00 MiB
llama_context: enumerating backends
llama_context: backend_ptrs.size() = 2
llama_context: max_nodes = 65536
llama_context: worst-case: n_tokens = 512, n_seqs = 1, n_outputs = 0
graph_reserve: reserving a graph for ubatch with n_tokens =  512, n_seqs =  1, n_outputs =  512
graph_reserve: reserving a graph for ubatch with n_tokens =    1, n_seqs =  1, n_outputs =    1
graph_reserve: reserving a graph for ubatch with n_tokens =  512, n_seqs =  1, n_outputs =  512
llama_context:      ROCm0 compute buffer size =   256.50 MiB
llama_context:  ROCm_Host compute buffer size =    10.01 MiB
llama_context: graph nodes  = 1014
llama_context: graph splits = 2
clear_adapter_lora: call
common_init_from_params: setting dry_penalty_last_n to ctx_size = 2048
srv          init: initializing slots, n_slots = 1
slot         init: id  0 | task -1 | new slot n_ctx_slot = 2048
slot        reset: id  0 | task -1 | 
main: model loaded
main: chat template, chat_template: {{- bos_token }}
{%- if custom_tools is defined %}
    {%- set tools = custom_tools %}
{%- endif %}
{%- if not tools_in_user_message is defined %}
    {%- set tools_in_user_message = true %}
{%- endif %}
{%- if not date_string is defined %}
    {%- if strftime_now is defined %}
        {%- set date_string = strftime_now("%d %b %Y") %}
    {%- else %}
        {%- set date_string = "26 Jul 2024" %}
    {%- endif %}
{%- endif %}
{%- if not tools is defined %}
    {%- set tools = none %}
{%- endif %}

{#- This block extracts the system message, so we can slot it into the right place. #}
{%- if messages[0]['role'] == 'system' %}
    {%- set system_message = messages[0]['content']|trim %}
    {%- set messages = messages[1:] %}
{%- else %}
    {%- set system_message = "" %}
{%- endif %}

{#- System message #}
{{- "<|start_header_id|>system<|end_header_id|>\n\n" }}
{%- if tools is not none %}
    {{- "Environment: ipython\n" }}
{%- endif %}
{{- "Cutting Knowledge Date: December 2023\n" }}
{{- "Today Date: " + date_string + "\n\n" }}
{%- if tools is not none and not tools_in_user_message %}
    {{- "You have access to the following functions. To call a function, please respond with JSON for a function call." }}
    {{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
    {{- "Do not use variables.\n\n" }}
    {%- for t in tools %}
        {{- t | tojson(indent=4) }}
        {{- "\n\n" }}
    {%- endfor %}
{%- endif %}
{{- system_message }}
{{- "<|eot_id|>" }}

{#- Custom tools are passed in a user message with some extra guidance #}
{%- if tools_in_user_message and not tools is none %}
    {#- Extract the first user message so we can plug it in here #}
    {%- if messages | length != 0 %}
        {%- set first_user_message = messages[0]['content']|trim %}
        {%- set messages = messages[1:] %}
    {%- else %}
        {{- raise_exception("Cannot put tools in the first user message when there's no first user message!") }}
{%- endif %}
    {{- '<|start_header_id|>user<|end_header_id|>\n\n' -}}
    {{- "Given the following functions, please respond with a JSON for a function call " }}
    {{- "with its proper arguments that best answers the given prompt.\n\n" }}
    {{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
    {{- "Do not use variables.\n\n" }}
    {%- for t in tools %}
        {{- t | tojson(indent=4) }}
        {{- "\n\n" }}
    {%- endfor %}
    {{- first_user_message + "<|eot_id|>"}}
{%- endif %}

{%- for message in messages %}
    {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}
        {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' }}
    {%- elif 'tool_calls' in message %}
        {%- if not message.tool_calls|length == 1 %}
            {{- raise_exception("This model only supports single tool-calls at once!") }}
        {%- endif %}
        {%- set tool_call = message.tool_calls[0].function %}
        {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
        {{- '{"name": "' + tool_call.name + '", ' }}
        {{- '"parameters": ' }}
        {{- tool_call.arguments | tojson }}
        {{- "}" }}
        {{- "<|eot_id|>" }}
    {%- elif message.role == "tool" or message.role == "ipython" %}
        {{- "<|start_header_id|>ipython<|end_header_id|>\n\n" }}
        {%- if message.content is mapping or message.content is iterable %}
            {{- message.content | tojson }}
        {%- else %}
            {{- message.content }}
        {%- endif %}
        {{- "<|eot_id|>" }}
    {%- endif %}
{%- endfor %}
{%- if add_generation_prompt %}
    {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' }}
{%- endif %}
, example_format: '<|start_header_id|>system<|end_header_id|>

Cutting Knowledge Date: December 2023
Today Date: 25 Jul 2025

You are a helpful assistant<|eot_id|><|start_header_id|>user<|end_header_id|>

Hello<|eot_id|><|start_header_id|>assistant<|end_header_id|>

Hi there<|eot_id|><|start_header_id|>user<|end_header_id|>

How are you?<|eot_id|><|start_header_id|>assistant<|end_header_id|>

'
main: server is listening on http://0.0.0.0:8080 - starting the main loop
que    start_loop: processing new tasks
que    start_loop: update slots
srv  update_slots: all slots are idle
srv  kv_cache_cle: clearing KV cache
que    start_loop: waiting for new tasks
srv  log_server_r: request: GET / 172.17.0.1 200
srv  log_server_r: request:  
srv  log_server_r: response: �
srv  log_server_r: request: GET /favicon.ico 172.17.0.1 404
srv  log_server_r: request:  
srv  log_server_r: response: {"error":{"code":404,"message":"File Not Found","type":"not_found_error"}}
srv  log_server_r: request: GET /props 172.17.0.1 200
srv  log_server_r: request:  
srv  log_server_r: response: {"default_generation_settings":{"id":0,"id_task":-1,"n_ctx":2048,"speculative":false,"is_processing":false,"params":{"n_predict":-1,"seed":4294967295,"temperature":0.800000011920929,"dynatemp_range":0.0,"dynatemp_exponent":1.0,"top_k":40,"top_p":0.949999988079071,"min_p":0.05000000074505806,"top_n_sigma":-1.0,"xtc_probability":0.0,"xtc_threshold":0.10000000149011612,"typical_p":1.0,"repeat_last_n":64,"repeat_penalty":1.0,"presence_penalty":0.0,"frequency_penalty":0.0,"dry_multiplier":0.0,"dry_base":1.75,"dry_allowed_length":2,"dry_penalty_last_n":2048,"dry_sequence_breakers":["\n",":","\"","*"],"mirostat":0,"mirostat_tau":5.0,"mirostat_eta":0.10000000149011612,"stop":[],"max_tokens":-1,"n_keep":0,"n_discard":0,"ignore_eos":false,"stream":true,"logit_bias":[],"n_probs":0,"min_keep":0,"grammar":"","grammar_lazy":false,"grammar_triggers":[],"preserved_tokens":[],"chat_format":"Content-only","reasoning_format":"none","reasoning_in_content":false,"thinking_forced_open":false,"samplers":["penalties","dry","top_n_sigma","top_k","typ_p","top_p","min_p","xtc","temperature"],"speculative.n_max":16,"speculative.n_min":0,"speculative.p_min":0.75,"timings_per_token":false,"post_sampling_probs":false,"lora":[]},"prompt":"","next_token":{"has_next_token":true,"has_new_line":false,"n_remain":-1,"n_decoded":0,"stopping_word":""}},"total_slots":1,"model_path":"/mnt/models/llama3.2","modalities":{"vision":false,"audio":false},"chat_template":"{{- bos_token }}\n{%- if custom_tools is defined %}\n    {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n    {%- set tools_in_user_message = true %}\n{%- endif %}\n{%- if not date_string is defined %}\n    {%- if strftime_now is defined %}\n        {%- set date_string = strftime_now(\"%d %b %Y\") %}\n    {%- else %}\n        {%- set date_string = \"26 Jul 2024\" %}\n    {%- endif %}\n{%- endif %}\n{%- if not tools is defined %}\n    {%- set tools = none %}\n{%- endif %}\n\n{#- This block extracts the system message, so we can slot it into the right place. #}\n{%- if messages[0]['role'] == 'system' %}\n    {%- set system_message = messages[0]['content']|trim %}\n    {%- set messages = messages[1:] %}\n{%- else %}\n    {%- set system_message = \"\" %}\n{%- endif %}\n\n{#- System message #}\n{{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n{%docker run --rm --label ai.ramalama.model=llama3.2:3b --label ai.ramalama.engine=docker --label ai.ramalama.runtime=llama.cpp --label ai.ramalama.port=8080 --label ai.ramalama.command=run --device /dev/dri --device /dev/kfd -e HIP_VISIBLE_DEVICES=1 -p 8080:8080 --security-opt=label=disable --cap-drop=all --security-opt=no-new-privileges -t -i --label ai.ramalama --name ramalama_IGngq1HF2u --env=HOME=/tmp --init --mount=type=bind,src=/home/mypc/.local/share/ramalama/store/ollama/library/llama3.2/blobs/sha256-dde5aa3fc5ffc17176b5e8bdc82f587b24b2678c6c66101bf7da77af9f7ccdff,destination=/mnt/models/llama3.2,ro --mount=type=bind,src=/home/mypc/.local/share/ramalama/store/ollama/library/llama3.2/blobs/sha256-34bb5ab01051a11372a91f95f3fbbc51173eed8e7f13ec395b9ae9b8bd0e242b,destination=/mnt/models/config.json,ro --mount=type=bind,src=/home/mypc/.local/share/ramalama/store/ollama/library/llama3.2/blobs/sha256-966de95ca8a62200913e3f8bfbf84c8494536f1b94b49166851e76644e966396,destination=/mnt/models/chat_template,ro quay.io/ramalama/rocm:latest llama-server --port 8080 --model /mnt/models/llama3.2 --no-warmup --jinja --log-colors --alias llama3.2:3b --ctx-size 2048 --temp 0.8 --cache-reuse 256 -v -ngl 999 --threads 12 --host 0.0.0.0 

ggml_cuda_init: GGML_CUDA_FORCE_MMQ:    no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 1 ROCm devices:
  Device 0: AMD Radeon Graphics, gfx1036 (0x1036), VMM: no, Wave Size: 32
build: 5764 (f667f1e6) with cc (GCC) 15.1.1 20250521 (Red Hat 15.1.1-2) for x86_64-redhat-linux
system info: n_threads = 12, n_threads_batch = 12, total_threads = 24

system_info: n_threads = 12 (n_threads_batch = 12) / 24 | ROCm : NO_VMM = 1 | PEER_MAX_BATCH_SIZE = 128 | CPU : SSE3 = 1 | SSSE3 = 1 | AVX = 1 | AVX2 = 1 | F16C = 1 | FMA = 1 | BMI2 = 1 | LLAMAFILE = 1 | OPENMP = 1 | REPACK = 1 | 

main: binding port with default address family
main: HTTP server is listening, hostname: 0.0.0.0, port: 8080, http threads: 23
main: loading model
srv    load_model: loading model '/mnt/models/llama3.2'
llama_model_load_from_file_impl: using device ROCm0 (AMD Radeon Graphics) - 31668 MiB free
llama_model_loader: loaded meta data with 30 key-value pairs and 255 tensors from /mnt/models/llama3.2 (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv   0:                       general.architecture str              = llama
llama_model_loader: - kv   1:                               general.type str              = model
llama_model_loader: - kv   2:                               general.name str              = Llama 3.2 3B Instruct
llama_model_loader: - kv   3:                           general.finetune str              = Instruct
llama_model_loader: - kv   4:                           general.basename str              = Llama-3.2
llama_model_loader: - kv   5:                         general.size_label str              = 3B
llama_model_loader: - kv   6:                               general.tags arr[str,6]       = ["facebook", "meta", "pytorch", "llam...
llama_model_loader: - kv   7:                          general.languages arr[str,8]       = ["en", "de", "fr", "it", "pt", "hi", ...
llama_model_loader: - kv   8:                          llama.block_count u32              = 28
llama_model_loader: - kv   9:                       llama.context_length u32              = 131072
llama_model_loader: - kv  10:                     llama.embedding_length u32              = 3072
llama_model_loader: - kv  11:                  llama.feed_forward_length u32              = 8192
llama_model_loader: - kv  12:                 llama.attention.head_count u32              = 24
llama_model_loader: - kv  13:              llama.attention.head_count_kv u32              = 8
llama_model_loader: - kv  14:                       llama.rope.freq_base f32              = 500000.000000
llama_model_loader: - kv  15:     llama.attention.layer_norm_rms_epsilon f32              = 0.000010
llama_model_loader: - kv  16:                 llama.attention.key_length u32              = 128
llama_model_loader: - kv  17:               llama.attention.value_length u32              = 128
llama_model_loader: - kv  18:                          general.file_type u32              = 15
llama_model_loader: - kv  19:                           llama.vocab_size u32              = 128256
llama_model_loader: - kv  20:                 llama.rope.dimension_count u32              = 128
llama_model_loader: - kv  21:                       tokenizer.ggml.model str              = gpt2
llama_model_loader: - kv  22:                         tokenizer.ggml.pre str              = llama-bpe
llama_model_loader: - kv  23:                      tokenizer.ggml.tokens arr[str,128256]  = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv  24:                  tokenizer.ggml.token_type arr[i32,128256]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv  25:                      tokenizer.ggml.merges arr[str,280147]  = ["Ġ Ġ", "Ġ ĠĠĠ", "ĠĠ ĠĠ", "...
llama_model_loader: - kv  26:                tokenizer.ggml.bos_token_id u32              = 128000
llama_model_loader: - kv  27:                tokenizer.ggml.eos_token_id u32              = 128009
llama_model_loader: - kv  28:                    tokenizer.chat_template str              = {{- bos_token }}\n{%- if custom_tools ...
llama_model_loader: - kv  29:               general.quantization_version u32              = 2
llama_model_loader: - type  f32:   58 tensors
llama_model_loader: - type q4_K:  168 tensors
llama_model_loader: - type q6_K:   29 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type   = Q4_K - Medium
print_info: file size   = 1.87 GiB (5.01 BPW) 
init_tokenizer: initializing tokenizer for type 2
load: control token: 128254 '<|reserved_special_token_246|>' is not marked as EOG
load: control token: 128249 '<|reserved_special_token_241|>' is not marked as EOG
load: control token: 128246 '<|reserved_special_token_238|>' is not marked as EOG
load: control token: 128243 '<|reserved_special_token_235|>' is not marked as EOG
load: control token: 128242 '<|reserved_special_token_234|>' is not marked as EOG
load: control token: 128241 '<|reserved_special_token_233|>' is not marked as EOG
load: control token: 128240 '<|reserved_special_token_232|>' is not marked as EOG
load: control token: 128235 '<|reserved_special_token_227|>' is not marked as EOG
load: control token: 128231 '<|reserved_special_token_223|>' is not marked as EOG
load: control token: 128230 '<|reserved_special_token_222|>' is not marked as EOG
load: control token: 128228 '<|reserved_special_token_220|>' is not marked as EOG
load: control token: 128225 '<|reserved_special_token_217|>' is not marked as EOG
load: control token: 128218 '<|reserved_special_token_210|>' is not marked as EOG
load: control token: 128214 '<|reserved_special_token_206|>' is not marked as EOG
load: control token: 128213 '<|reserved_special_token_205|>' is not marked as EOG
load: control token: 128207 '<|reserved_special_token_199|>' is not marked as EOG
load: control token: 128206 '<|reserved_special_token_198|>' is not marked as EOG
load: control token: 128204 '<|reserved_special_token_196|>' is not marked as EOG
load: control token: 128200 '<|reserved_special_token_192|>' is not marked as EOG
load: control token: 128199 '<|reserved_special_token_191|>' is not marked as EOG
load: control token: 128198 '<|reserved_special_token_190|>' is not marked as EOG
load: control token: 128196 '<|reserved_special_token_188|>' is not marked as EOG
load: control token: 128194 '<|reserved_special_token_186|>' is not marked as EOG
load: control token: 128193 '<|reserved_special_token_185|>' is not marked as EOG
load: control token: 128188 '<|reserved_special_token_180|>' is not marked as EOG
load: control token: 128187 '<|reserved_special_token_179|>' is not marked as EOG
load: control token: 128185 '<|reserved_special_token_177|>' is not marked as EOG
load: control token: 128184 '<|reserved_special_token_176|>' is not marked as EOG
load: control token: 128180 '<|reserved_special_token_172|>' is not marked as EOG
load: control token: 128179 '<|reserved_special_token_171|>' is not marked as EOG
load: control token: 128178 '<|reserved_special_token_170|>' is not marked as EOG
load: control token: 128177 '<|reserved_special_token_169|>' is not marked as EOG
load: control token: 128176 '<|reserved_special_token_168|>' is not marked as EOG
load: control token: 128175 '<|reserved_special_token_167|>' is not marked as EOG
load: control token: 128171 '<|reserved_special_token_163|>' is not marked as EOG
load: control token: 128170 '<|reserved_special_token_162|>' is not marked as EOG
load: control token: 128169 '<|reserved_special_token_161|>' is not marked as EOG
load: control token: 128168 '<|reserved_special_token_160|>' is not marked as EOG
load: control token: 128165 '<|reserved_special_token_157|>' is not marked as EOG
load: control token: 128162 '<|reserved_special_token_154|>' is not marked as EOG
load: control token: 128158 '<|reserved_special_token_150|>' is not marked as EOG
load: control token: 128156 '<|reserved_special_token_148|>' is not marked as EOG
load: control token: 128155 '<|reserved_special_token_147|>' is not marked as EOG
load: control token: 128154 '<|reserved_special_token_146|>' is not marked as EOG
load: control token: 128151 '<|reserved_special_token_143|>' is not marked as EOG
load: control token: 128149 '<|reserved_special_token_141|>' is not marked as EOG
load: control token: 128147 '<|reserved_special_token_139|>' is not marked as EOG
load: control token: 128146 '<|reserved_special_token_138|>' is not marked as EOG
load: control token: 128144 '<|reserved_special_token_136|>' is not marked as EOG
load: control token: 128142 '<|reserved_special_token_134|>' is not marked as EOG
load: control token: 128141 '<|reserved_special_token_133|>' is not marked as EOG
load: control token: 128138 '<|reserved_special_token_130|>' is not marked as EOG
load: control token: 128136 '<|reserved_special_token_128|>' is not marked as EOG
load: control token: 128135 '<|reserved_special_token_127|>' is not marked as EOG
load: control token: 128134 '<|reserved_special_token_126|>' is not marked as EOG
load: control token: 128133 '<|reserved_special_token_125|>' is not marked as EOG
load: control token: 128131 '<|reserved_special_token_123|>' is not marked as EOG
load: control token: 128128 '<|reserved_special_token_120|>' is not marked as EOG
load: control token: 128124 '<|reserved_special_token_116|>' is not marked as EOG
load: control token: 128123 '<|reserved_special_token_115|>' is not marked as EOG
load: control token: 128122 '<|reserved_special_token_114|>' is not marked as EOG
load: control token: 128119 '<|reserved_special_token_111|>' is not marked as EOG
load: control token: 128115 '<|reserved_special_token_107|>' is not marked as EOG
load: control token: 128112 '<|reserved_special_token_104|>' is not marked as EOG
load: control token: 128110 '<|reserved_special_token_102|>' is not marked as EOG
load: control token: 128109 '<|reserved_special_token_101|>' is not marked as EOG
load: control token: 128108 '<|reserved_special_token_100|>' is not marked as EOG
load: control token: 128106 '<|reserved_special_token_98|>' is not marked as EOG
load: control token: 128103 '<|reserved_special_token_95|>' is not marked as EOG
load: control token: 128102 '<|reserved_special_token_94|>' is not marked as EOG
load: control token: 128101 '<|reserved_special_token_93|>' is not marked as EOG
load: control token: 128097 '<|reserved_special_token_89|>' is not marked as EOG
load: control token: 128091 '<|reserved_special_token_83|>' is not marked as EOG
load: control token: 128090 '<|reserved_special_token_82|>' is not marked as EOG
load: control token: 128089 '<|reserved_special_token_81|>' is not marked as EOG
load: control token: 128087 '<|reserved_special_token_79|>' is not marked as EOG
load: control token: 128085 '<|reserved_special_token_77|>' is not marked as EOG
load: control token: 128081 '<|reserved_special_token_73|>' is not marked as EOG
load: control token: 128078 '<|reserved_special_token_70|>' is not marked as EOG
load: control token: 128076 '<|reserved_special_token_68|>' is not marked as EOG
load: control token: 128075 '<|reserved_special_token_67|>' is not marked as EOG
load: control token: 128073 '<|reserved_special_token_65|>' is not marked as EOG
load: control token: 128068 '<|reserved_special_token_60|>' is not marked as EOG
load: control token: 128067 '<|reserved_special_token_59|>' is not marked as EOG
load: control token: 128065 '<|reserved_special_token_57|>' is not marked as EOG
load: control token: 128063 '<|reserved_special_token_55|>' is not marked as EOG
load: control token: 128062 '<|reserved_special_token_54|>' is not marked as EOG
load: control token: 128060 '<|reserved_special_token_52|>' is not marked as EOG
load: control token: 128059 '<|reserved_special_token_51|>' is not marked as EOG
load: control token: 128057 '<|reserved_special_token_49|>' is not marked as EOG
load: control token: 128054 '<|reserved_special_token_46|>' is not marked as EOG
load: control token: 128046 '<|reserved_special_token_38|>' is not marked as EOG
load: control token: 128045 '<|reserved_special_token_37|>' is not marked as EOG
load: control token: 128044 '<|reserved_special_token_36|>' is not marked as EOG
load: control token: 128043 '<|reserved_special_token_35|>' is not marked as EOG
load: control token: 128038 '<|reserved_special_token_30|>' is not marked as EOG
load: control token: 128036 '<|reserved_special_token_28|>' is not marked as EOG
load: control token: 128035 '<|reserved_special_token_27|>' is not marked as EOG
load: control token: 128032 '<|reserved_special_token_24|>' is not marked as EOG
load: control token: 128028 '<|reserved_special_token_20|>' is not marked as EOG
load: control token: 128027 '<|reserved_special_token_19|>' is not marked as EOG
load: control token: 128024 '<|reserved_special_token_16|>' is not marked as EOG
load: control token: 128023 '<|reserved_special_token_15|>' is not marked as EOG
load: control token: 128022 '<|reserved_special_token_14|>' is not marked as EOG
load: control token: 128021 '<|reserved_special_token_13|>' is not marked as EOG
load: control token: 128018 '<|reserved_special_token_10|>' is not marked as EOG
load: control token: 128016 '<|reserved_special_token_8|>' is not marked as EOG
load: control token: 128015 '<|reserved_special_token_7|>' is not marked as EOG
load: control token: 128013 '<|reserved_special_token_5|>' is not marked as EOG
load: control token: 128011 '<|reserved_special_token_3|>' is not marked as EOG
load: control token: 128005 '<|reserved_special_token_2|>' is not marked as EOG
load: control token: 128004 '<|finetune_right_pad_id|>' is not marked as EOG
load: control token: 128002 '<|reserved_special_token_0|>' is not marked as EOG
load: control token: 128252 '<|reserved_special_token_244|>' is not marked as EOG
load: control token: 128190 '<|reserved_special_token_182|>' is not marked as EOG
load: control token: 128183 '<|reserved_special_token_175|>' is not marked as EOG
load: control token: 128137 '<|reserved_special_token_129|>' is not marked as EOG
load: control token: 128182 '<|reserved_special_token_174|>' is not marked as EOG
load: control token: 128040 '<|reserved_special_token_32|>' is not marked as EOG
load: control token: 128048 '<|reserved_special_token_40|>' is not marked as EOG
load: control token: 128092 '<|reserved_special_token_84|>' is not marked as EOG
load: control token: 128215 '<|reserved_special_token_207|>' is not marked as EOG
load: control token: 128107 '<|reserved_special_token_99|>' is not marked as EOG
load: control token: 128208 '<|reserved_special_token_200|>' is not marked as EOG
load: control token: 128145 '<|reserved_special_token_137|>' is not marked as EOG
load: control token: 128031 '<|reserved_special_token_23|>' is not marked as EOG
load: control token: 128129 '<|reserved_special_token_121|>' is not marked as EOG
load: control token: 128201 '<|reserved_special_token_193|>' is not marked as EOG
load: control token: 128074 '<|reserved_special_token_66|>' is not marked as EOG
load: control token: 128095 '<|reserved_special_token_87|>' is not marked as EOG
load: control token: 128186 '<|reserved_special_token_178|>' is not marked as EOG
load: control token: 128143 '<|reserved_special_token_135|>' is not marked as EOG
load: control token: 128229 '<|reserved_special_token_221|>' is not marked as EOG
load: control token: 128007 '<|end_header_id|>' is not marked as EOG
load: control token: 128055 '<|reserved_special_token_47|>' is not marked as EOG
load: control token: 128056 '<|reserved_special_token_48|>' is not marked as EOG
load: control token: 128061 '<|reserved_special_token_53|>' is not marked as EOG
load: control token: 128153 '<|reserved_special_token_145|>' is not marked as EOG
load: control token: 128152 '<|reserved_special_token_144|>' is not marked as EOG
load: control token: 128212 '<|reserved_special_token_204|>' is not marked as EOG
load: control token: 128172 '<|reserved_special_token_164|>' is not marked as EOG
load: control token: 128160 '<|reserved_special_token_152|>' is not marked as EOG
load: control token: 128041 '<|reserved_special_token_33|>' is not marked as EOG
load: control token: 128181 '<|reserved_special_token_173|>' is not marked as EOG
load: control token: 128094 '<|reserved_special_token_86|>' is not marked as EOG
load: control token: 128118 '<|reserved_special_token_110|>' is not marked as EOG
load: control token: 128236 '<|reserved_special_token_228|>' is not marked as EOG
load: control token: 128148 '<|reserved_special_token_140|>' is not marked as EOG
load: control token: 128042 '<|reserved_special_token_34|>' is not marked as EOG
load: control token: 128139 '<|reserved_special_token_131|>' is not marked as EOG
load: control token: 128173 '<|reserved_special_token_165|>' is not marked as EOG
load: control token: 128239 '<|reserved_special_token_231|>' is not marked as EOG
load: control token: 128157 '<|reserved_special_token_149|>' is not marked as EOG
load: control token: 128052 '<|reserved_special_token_44|>' is not marked as EOG
load: control token: 128026 '<|reserved_special_token_18|>' is not marked as EOG
load: control token: 128003 '<|reserved_special_token_1|>' is not marked as EOG
load: control token: 128019 '<|reserved_special_token_11|>' is not marked as EOG
load: control token: 128116 '<|reserved_special_token_108|>' is not marked as EOG
load: control token: 128161 '<|reserved_special_token_153|>' is not marked as EOG
load: control token: 128226 '<|reserved_special_token_218|>' is not marked as EOG
load: control token: 128159 '<|reserved_special_token_151|>' is not marked as EOG
load: control token: 128012 '<|reserved_special_token_4|>' is not marked as EOG
load: control token: 128088 '<|reserved_special_token_80|>' is not marked as EOG
load: control token: 128163 '<|reserved_special_token_155|>' is not marked as EOG
load: control token: 128113 '<|reserved_special_token_105|>' is not marked as EOG
load: control token: 128250 '<|reserved_special_token_242|>' is not marked as EOG
load: control token: 128125 '<|reserved_special_token_117|>' is not marked as EOG
load: control token: 128053 '<|reserved_special_token_45|>' is not marked as EOG
load: control token: 128224 '<|reserved_special_token_216|>' is not marked as EOG
load: control token: 128247 '<|reserved_special_token_239|>' is not marked as EOG
load: control token: 128251 '<|reserved_special_token_243|>' is not marked as EOG
load: control token: 128216 '<|reserved_special_token_208|>' is not marked as EOG
load: control token: 128006 '<|start_header_id|>' is not marked as EOG
load: control token: 128211 '<|reserved_special_token_203|>' is not marked as EOG
load: control token: 128077 '<|reserved_special_token_69|>' is not marked as EOG
load: control token: 128237 '<|reserved_special_token_229|>' is not marked as EOG
load: control token: 128086 '<|reserved_special_token_78|>' is not marked as EOG
load: control token: 128227 '<|reserved_special_token_219|>' is not marked as EOG
load: control token: 128058 '<|reserved_special_token_50|>' is not marked as EOG
load: control token: 128100 '<|reserved_special_token_92|>' is not marked as EOG
load: control token: 128209 '<|reserved_special_token_201|>' is not marked as EOG
load: control token: 128084 '<|reserved_special_token_76|>' is not marked as EOG
load: control token: 128071 '<|reserved_special_token_63|>' is not marked as EOG
load: control token: 128070 '<|reserved_special_token_62|>' is not marked as EOG
load: control token: 128049 '<|reserved_special_token_41|>' is not marked as EOG
load: control token: 128197 '<|reserved_special_token_189|>' is not marked as EOG
load: control token: 128072 '<|reserved_special_token_64|>' is not marked as EOG
load: control token: 128000 '<|begin_of_text|>' is not marked as EOG
load: control token: 128223 '<|reserved_special_token_215|>' is not marked as EOG
load: control token: 128217 '<|reserved_special_token_209|>' is not marked as EOG
load: control token: 128111 '<|reserved_special_token_103|>' is not marked as EOG
load: control token: 128203 '<|reserved_special_token_195|>' is not marked as EOG
load: control token: 128051 '<|reserved_special_token_43|>' is not marked as EOG
load: control token: 128030 '<|reserved_special_token_22|>' is not marked as EOG
load: control token: 128117 '<|reserved_special_token_109|>' is not marked as EOG
load: control token: 128010 '<|python_tag|>' is not marked as EOG
load: control token: 128238 '<|reserved_special_token_230|>' is not marked as EOG
load: control token: 128255 '<|reserved_special_token_247|>' is not marked as EOG
load: control token: 128202 '<|reserved_special_token_194|>' is not marked as EOG
load: control token: 128132 '<|reserved_special_token_124|>' is not marked as EOG
load: control token: 128248 '<|reserved_special_token_240|>' is not marked as EOG
load: control token: 128167 '<|reserved_special_token_159|>' is not marked as EOG
load: control token: 128127 '<|reserved_special_token_119|>' is not marked as EOG
load: control token: 128105 '<|reserved_special_token_97|>' is not marked as EOG
load: control token: 128039 '<|reserved_special_token_31|>' is not marked as EOG
load: control token: 128232 '<|reserved_special_token_224|>' is not marked as EOG
load: control token: 128166 '<|reserved_special_token_158|>' is not marked as EOG
load: control token: 128130 '<|reserved_special_token_122|>' is not marked as EOG
load: control token: 128114 '<|reserved_special_token_106|>' is not marked as EOG
load: control token: 128234 '<|reserved_special_token_226|>' is not marked as EOG
load: control token: 128191 '<|reserved_special_token_183|>' is not marked as EOG
load: control token: 128064 '<|reserved_special_token_56|>' is not marked as EOG
load: control token: 128140 '<|reserved_special_token_132|>' is not marked as EOG
load: control token: 128096 '<|reserved_special_token_88|>' is not marked as EOG
load: control token: 128098 '<|reserved_special_token_90|>' is not marked as EOG
load: control token: 128192 '<|reserved_special_token_184|>' is not marked as EOG
load: control token: 128093 '<|reserved_special_token_85|>' is not marked as EOG
load: control token: 128150 '<|reserved_special_token_142|>' is not marked as EOG
load: control token: 128222 '<|reserved_special_token_214|>' is not marked as EOG
load: control token: 128233 '<|reserved_special_token_225|>' is not marked as EOG
load: control token: 128220 '<|reserved_special_token_212|>' is not marked as EOG
load: control token: 128034 '<|reserved_special_token_26|>' is not marked as EOG
load: control token: 128033 '<|reserved_special_token_25|>' is not marked as EOG
load: control token: 128253 '<|reserved_special_token_245|>' is not marked as EOG
load: control token: 128195 '<|reserved_special_token_187|>' is not marked as EOG
load: control token: 128099 '<|reserved_special_token_91|>' is not marked as EOG
load: control token: 128189 '<|reserved_special_token_181|>' is not marked as EOG
load: control token: 128210 '<|reserved_special_token_202|>' is not marked as EOG
load: control token: 128174 '<|reserved_special_token_166|>' is not marked as EOG
load: control token: 128083 '<|reserved_special_token_75|>' is not marked as EOG
load: control token: 128080 '<|reserved_special_token_72|>' is not marked as EOG
load: control token: 128104 '<|reserved_special_token_96|>' is not marked as EOG
load: control token: 128082 '<|reserved_special_token_74|>' is not marked as EOG
load: control token: 128219 '<|reserved_special_token_211|>' is not marked as EOG
load: control token: 128017 '<|reserved_special_token_9|>' is not marked as EOG
load: control token: 128050 '<|reserved_special_token_42|>' is not marked as EOG
load: control token: 128205 '<|reserved_special_token_197|>' is not marked as EOG
load: control token: 128047 '<|reserved_special_token_39|>' is not marked as EOG
load: control token: 128164 '<|reserved_special_token_156|>' is not marked as EOG
load: control token: 128020 '<|reserved_special_token_12|>' is not marked as EOG
load: control token: 128069 '<|reserved_special_token_61|>' is not marked as EOG
load: control token: 128245 '<|reserved_special_token_237|>' is not marked as EOG
load: control token: 128121 '<|reserved_special_token_113|>' is not marked as EOG
load: control token: 128079 '<|reserved_special_token_71|>' is not marked as EOG
load: control token: 128037 '<|reserved_special_token_29|>' is not marked as EOG
load: control token: 128244 '<|reserved_special_token_236|>' is not marked as EOG
load: control token: 128029 '<|reserved_special_token_21|>' is not marked as EOG
load: control token: 128221 '<|reserved_special_token_213|>' is not marked as EOG
load: control token: 128066 '<|reserved_special_token_58|>' is not marked as EOG
load: control token: 128120 '<|reserved_special_token_112|>' is not marked as EOG
load: control token: 128014 '<|reserved_special_token_6|>' is not marked as EOG
load: control token: 128025 '<|reserved_special_token_17|>' is not marked as EOG
load: control token: 128126 '<|reserved_special_token_118|>' is not marked as EOG
load: special tokens cache size = 256
load: token to piece cache size = 0.7999 MB
print_info: arch             = llama
print_info: vocab_only       = 0
print_info: n_ctx_train      = 131072
print_info: n_embd           = 3072
print_info: n_layer          = 28
print_info: n_head           = 24
print_info: n_head_kv        = 8
print_info: n_rot            = 128
print_info: n_swa            = 0
print_info: is_swa_any       = 0
print_info: n_embd_head_k    = 128
print_info: n_embd_head_v    = 128
print_info: n_gqa            = 3
print_info: n_embd_k_gqa     = 1024
print_info: n_embd_v_gqa     = 1024
print_info: f_norm_eps       = 0.0e+00
print_info: f_norm_rms_eps   = 1.0e-05
print_info: f_clamp_kqv      = 0.0e+00
print_info: f_max_alibi_bias = 0.0e+00
print_info: f_logit_scale    = 0.0e+00
print_info: f_attn_scale     = 0.0e+00
print_info: n_ff             = 8192
print_info: n_expert         = 0
print_info: n_expert_used    = 0
print_info: causal attn      = 1
print_info: pooling type     = 0
print_info: rope type        = 0
print_info: rope scaling     = linear
print_info: freq_base_train  = 500000.0
print_info: freq_scale_train = 1
print_info: n_ctx_orig_yarn  = 131072
print_info: rope_finetuned   = unknown
print_info: ssm_d_conv       = 0
print_info: ssm_d_inner      = 0
print_info: ssm_d_state      = 0
print_info: ssm_dt_rank      = 0
print_info: ssm_dt_b_c_rms   = 0
print_info: model type       = 3B
print_info: model params     = 3.21 B
print_info: general.name     = Llama 3.2 3B Instruct
print_info: vocab type       = BPE
print_info: n_vocab          = 128256
print_info: n_merges         = 280147
print_info: BOS token        = 128000 '<|begin_of_text|>'
print_info: EOS token        = 128009 '<|eot_id|>'
print_info: EOT token        = 128009 '<|eot_id|>'
print_info: EOM token        = 128008 '<|eom_id|>'
print_info: LF token         = 198 'Ċ'
print_info: EOG token        = 128001 '<|end_of_text|>'
print_info: EOG token        = 128008 '<|eom_id|>'
print_info: EOG token        = 128009 '<|eot_id|>'
print_info: max token length = 256
load_tensors: loading model tensors, this can take a while... (mmap = true)
load_tensors: layer   0 assigned to device ROCm0, is_swa = 0
load_tensors: layer   1 assigned to device ROCm0, is_swa = 0
load_tensors: layer   2 assigned to device ROCm0, is_swa = 0
load_tensors: layer   3 assigned to device ROCm0, is_swa = 0
load_tensors: layer   4 assigned to device ROCm0, is_swa = 0
load_tensors: layer   5 assigned to device ROCm0, is_swa = 0
load_tensors: layer   6 assigned to device ROCm0, is_swa = 0
load_tensors: layer   7 assigned to device ROCm0, is_swa = 0
load_tensors: layer   8 assigned to device ROCm0, is_swa = 0
load_tensors: layer   9 assigned to device ROCm0, is_swa = 0
load_tensors: layer  10 assigned to device ROCm0, is_swa = 0
load_tensors: layer  11 assigned to device ROCm0, is_swa = 0
load_tensors: layer  12 assigned to device ROCm0, is_swa = 0
load_tensors: layer  13 assigned to device ROCm0, is_swa = 0
load_tensors: layer  14 assigned to device ROCm0, is_swa = 0
load_tensors: layer  15 assigned to device ROCm0, is_swa = 0
load_tensors: layer  16 assigned to device ROCm0, is_swa = 0
load_tensors: layer  17 assigned to device ROCm0, is_swa = 0
load_tensors: layer  18 assigned to device ROCm0, is_swa = 0
load_tensors: layer  19 assigned to device ROCm0, is_swa = 0
load_tensors: layer  20 assigned to device ROCm0, is_swa = 0
load_tensors: layer  21 assigned to device ROCm0, is_swa = 0
load_tensors: layer  22 assigned to device ROCm0, is_swa = 0
load_tensors: layer  23 assigned to device ROCm0, is_swa = 0
load_tensors: layer  24 assigned to device ROCm0, is_swa = 0
load_tensors: layer  25 assigned to device ROCm0, is_swa = 0
load_tensors: layer  26 assigned to device ROCm0, is_swa = 0
load_tensors: layer  27 assigned to device ROCm0, is_swa = 0
load_tensors: layer  28 assigned to device ROCm0, is_swa = 0
load_tensors: tensor 'token_embd.weight' (q6_K) (and 0 others) cannot be used with preferred buffer type ROCm_Host, using CPU instead
load_tensors: offloading 28 repeating layers to GPU
load_tensors: offloading output layer to GPU
load_tensors: offloaded 29/29 layers to GPU
load_tensors:   CPU_Mapped model buffer size =   308.23 MiB
load_tensors:        ROCm0 model buffer size =  1918.35 MiB
...........................................................................
llama_context: constructing llama_context
llama_context: n_seq_max     = 1
llama_context: n_ctx         = 2048
llama_context: n_ctx_per_seq = 2048
llama_context: n_batch       = 2048
llama_context: n_ubatch      = 512
llama_context: causal_attn   = 1
llama_context: flash_attn    = 0
llama_context: freq_base     = 500000.0
llama_context: freq_scale    = 1
llama_context: n_ctx_per_seq (2048) < n_ctx_train (131072) -- the full capacity of the model will not be utilized
set_abort_callback: call
llama_context:  ROCm_Host  output buffer size =     0.49 MiB
create_memory: n_ctx = 2048 (padded)
llama_kv_cache_unified: layer   0: dev = ROCm0
llama_kv_cache_unified: layer   1: dev = ROCm0
llama_kv_cache_unified: layer   2: dev = ROCm0
llama_kv_cache_unified: layer   3: dev = ROCm0
llama_kv_cache_unified: layer   4: dev = ROCm0
llama_kv_cache_unified: layer   5: dev = ROCm0
llama_kv_cache_unified: layer   6: dev = ROCm0
llama_kv_cache_unified: layer   7: dev = ROCm0
llama_kv_cache_unified: layer   8: dev = ROCm0
llama_kv_cache_unified: layer   9: dev = ROCm0
llama_kv_cache_unified: layer  10: dev = ROCm0
llama_kv_cache_unified: layer  11: dev = ROCm0
llama_kv_cache_unified: layer  12: dev = ROCm0
llama_kv_cache_unified: layer  13: dev = ROCm0
llama_kv_cache_unified: layer  14: dev = ROCm0
llama_kv_cache_unified: layer  15: dev = ROCm0
llama_kv_cache_unified: layer  16: dev = ROCm0
llama_kv_cache_unified: layer  17: dev = ROCm0
llama_kv_cache_unified: layer  18: dev = ROCm0
llama_kv_cache_unified: layer  19: dev = ROCm0
llama_kv_cache_unified: layer  20: dev = ROCm0
llama_kv_cache_unified: layer  21: dev = ROCm0
llama_kv_cache_unified: layer  22: dev = ROCm0
llama_kv_cache_unified: layer  23: dev = ROCm0
llama_kv_cache_unified: layer  24: dev = ROCm0
llama_kv_cache_unified: layer  25: dev = ROCm0
llama_kv_cache_unified: layer  26: dev = ROCm0
llama_kv_cache_unified: layer  27: dev = ROCm0
llama_kv_cache_unified:      ROCm0 KV buffer size =   224.00 MiB
llama_kv_cache_unified: size =  224.00 MiB (  2048 cells,  28 layers,  1 seqs), K (f16):  112.00 MiB, V (f16):  112.00 MiB
llama_context: enumerating backends
llama_context: backend_ptrs.size() = 2
llama_context: max_nodes = 65536
llama_context: worst-case: n_tokens = 512, n_seqs = 1, n_outputs = 0
graph_reserve: reserving a graph for ubatch with n_tokens =  512, n_seqs =  1, n_outputs =  512
graph_reserve: reserving a graph for ubatch with n_tokens =    1, n_seqs =  1, n_outputs =    1
graph_reserve: reserving a graph for ubatch with n_tokens =  512, n_seqs =  1, n_outputs =  512
llama_context:      ROCm0 compute buffer size =   256.50 MiB
llama_context:  ROCm_Host compute buffer size =    10.01 MiB
llama_context: graph nodes  = 1014
llama_context: graph splits = 2
clear_adapter_lora: call
common_init_from_params: setting dry_penalty_last_n to ctx_size = 2048
srv          init: initializing slots, n_slots = 1
slot         init: id  0 | task -1 | new slot n_ctx_slot = 2048
slot        reset: id  0 | task -1 | 
main: model loaded
main: chat template, chat_template: {{- bos_token }}
{%- if custom_tools is defined %}
    {%- set tools = custom_tools %}
{%- endif %}
{%- if not tools_in_user_message is defined %}
    {%- set tools_in_user_message = true %}
{%- endif %}
{%- if not date_string is defined %}
    {%- if strftime_now is defined %}
        {%- set date_string = strftime_now("%d %b %Y") %}
    {%- else %}
        {%- set date_string = "26 Jul 2024" %}
    {%- endif %}
{%- endif %}
{%- if not tools is defined %}
    {%- set tools = none %}
{%- endif %}

{#- This block extracts the system message, so we can slot it into the right place. #}
{%- if messages[0]['role'] == 'system' %}
    {%- set system_message = messages[0]['content']|trim %}
    {%- set messages = messages[1:] %}
{%- else %}
    {%- set system_message = "" %}
{%- endif %}

{#- System message #}
{{- "<|start_header_id|>system<|end_header_id|>\n\n" }}
{%- if tools is not none %}
    {{- "Environment: ipython\n" }}
{%- endif %}
{{- "Cutting Knowledge Date: December 2023\n" }}
{{- "Today Date: " + date_string + "\n\n" }}
{%- if tools is not none and not tools_in_user_message %}
    {{- "You have access to the following functions. To call a function, please respond with JSON for a function call." }}
    {{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
    {{- "Do not use variables.\n\n" }}
    {%- for t in tools %}
        {{- t | tojson(indent=4) }}
        {{- "\n\n" }}
    {%- endfor %}
{%- endif %}
{{- system_message }}
{{- "<|eot_id|>" }}

{#- Custom tools are passed in a user message with some extra guidance #}
{%- if tools_in_user_message and not tools is none %}
    {#- Extract the first user message so we can plug it in here #}
    {%- if messages | length != 0 %}
        {%- set first_user_message = messages[0]['content']|trim %}
        {%- set messages = messages[1:] %}
    {%- else %}
        {{- raise_exception("Cannot put tools in the first user message when there's no first user message!") }}
{%- endif %}
    {{- '<|start_header_id|>user<|end_header_id|>\n\n' -}}
    {{- "Given the following functions, please respond with a JSON for a function call " }}
    {{- "with its proper arguments that best answers the given prompt.\n\n" }}
    {{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
    {{- "Do not use variables.\n\n" }}
    {%- for t in tools %}
        {{- t | tojson(indent=4) }}
        {{- "\n\n" }}
    {%- endfor %}
    {{- first_user_message + "<|eot_id|>"}}
{%- endif %}

{%- for message in messages %}
    {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}
        {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' }}
    {%- elif 'tool_calls' in message %}
        {%- if not message.tool_calls|length == 1 %}
            {{- raise_exception("This model only supports single tool-calls at once!") }}
        {%- endif %}
        {%- set tool_call = message.tool_calls[0].function %}
        {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
        {{- '{"name": "' + tool_call.name + '", ' }}
        {{- '"parameters": ' }}
        {{- tool_call.arguments | tojson }}
        {{- "}" }}
        {{- "<|eot_id|>" }}
    {%- elif message.role == "tool" or message.role == "ipython" %}
        {{- "<|start_header_id|>ipython<|end_header_id|>\n\n" }}
        {%- if message.content is mapping or message.content is iterable %}
            {{- message.content | tojson }}
        {%- else %}
            {{- message.content }}
        {%- endif %}
        {{- "<|eot_id|>" }}
    {%- endif %}
{%- endfor %}
{%- if add_generation_prompt %}
    {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' }}
{%- endif %}
, example_format: '<|start_header_id|>system<|end_header_id|>

Cutting Knowledge Date: December 2023
Today Date: 25 Jul 2025

You are a helpful assistant<|eot_id|><|start_header_id|>user<|end_header_id|>

Hello<|eot_id|><|start_header_id|>assistant<|end_header_id|>

Hi there<|eot_id|><|start_header_id|>user<|end_header_id|>

How are you?<|eot_id|><|start_header_id|>assistant<|end_header_id|>

'
main: server is listening on http://0.0.0.0:8080 - starting the main loop
que    start_loop: processing new tasks
que    start_loop: update slots
srv  update_slots: all slots are idle
srv  kv_cache_cle: clearing KV cache
que    start_loop: waiting for new tasks
srv  log_server_r: request: GET / 172.17.0.1 200
srv  log_server_r: request:  
srv  log_server_r: response: �
srv  log_server_r: request: GET /favicon.ico 172.17.0.1 404
srv  log_server_r: request:  
srv  log_server_r: response: {"error":{"code":404,"message":"File Not Found","type":"not_found_error"}}
srv  log_server_r: request: GET /props 172.17.0.1 200
srv  log_server_r: request:  
srv  log_server_r: response: {"default_generation_settings":{"id":0,"id_task":-1,"n_ctx":2048,"speculative":false,"is_processing":false,"params":{"n_predict":-1,"seed":4294967295,"temperature":0.800000011920929,"dynatemp_range":0.0,"dynatemp_exponent":1.0,"top_k":40,"top_p":0.949999988079071,"min_p":0.05000000074505806,"top_n_sigma":-1.0,"xtc_probability":0.0,"xtc_threshold":0.10000000149011612,"typical_p":1.0,"repeat_last_n":64,"repeat_penalty":1.0,"presence_penalty":0.0,"frequency_penalty":0.0,"dry_multiplier":0.0,"dry_base":1.75,"dry_allowed_length":2,"dry_penalty_last_n":2048,"dry_sequence_breakers":["\n",":","\"","*"],"mirostat":0,"mirostat_tau":5.0,"mirostat_eta":0.10000000149011612,"stop":[],"max_tokens":-1,"n_keep":0,"n_discard":0,"ignore_eos":false,"stream":true,"logit_bias":[],"n_probs":0,"min_keep":0,"grammar":"","grammar_lazy":false,"grammar_triggers":[],"preserved_tokens":[],"chat_format":"Content-only","reasoning_format":"none","reasoning_in_content":false,"thinking_forced_open":false,"samplers":["penalties","dry","top_n_sigma","top_k","typ_p","top_p","min_p","xtc","temperature"],"speculative.n_max":16,"speculative.n_min":0,"speculative.p_min":0.75,"timings_per_token":false,"post_sampling_probs":false,"lora":[]},"prompt":"","next_token":{"has_next_token":true,"has_new_line":false,"n_remain":-1,"n_decoded":0,"stopping_word":""}},"total_slots":1,"model_path":"/mnt/models/llama3.2","modalities":{"vision":false,"audio":false},"chat_template":"{{- bos_token }}\n{%- if custom_tools is defined %}\n    {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n    {%- set tools_in_user_message = true %}\n{%- endif %}\n{%- if not date_string is defined %}\n    {%- if strftime_now is defined %}\n        {%- set date_string = strftime_now(\"%d %b %Y\") %}\n    {%- else %}\n        {%- set date_string = \"26 Jul 2024\" %}\n    {%- endif %}\n{%- endif %}\n{%- if not tools is defined %}\n    {%- set tools = none %}\n{%- endif %}\n\n{#- This block extracts the system message, so we can slot it into the right place. #}\n{%- if messages[0]['role'] == 'system' %}\n    {%- set system_message = messages[0]['content']|trim %}\n    {%- set messages = messages[1:] %}\n{%- else %}\n    {%- set system_message = \"\" %}\n{%- endif %}\n\n{#- System message #}\n{{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n{%- if tools is not none %}\n    {{- \"Environment: ipython\\n\" }}\n{%- endif %}\n{{- \"Cutting Knowledge Date: December 2023\\n\" }}\n{{- \"Today Date: \" + date_string + \"\\n\\n\" }}\n{%- if tools is not none and not tools_in_user_message %}\n    {{- \"You have access to the following functions. To call a function, please respond with JSON for a function call.\" }}\n    {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n    {{- \"Do not use variables.\\n\\n\" }}\n    {%- for t in tools %}\n        {{- t | tojson(indent=4) }}\n        {{- \"\\n\\n\" }}\n    {%- endfor %}\n{%- endif %}\n{{- system_message }}\n{{- \"<|eot_id|>\" }}\n\n{#- Custom tools are passed in a user message with some extra guidance #}\n{%- if tools_in_user_message and not tools is none %}\n    {#- Extract the first user message so we can plug it in here #}\n    {%- if messages | length != 0 %}\n        {%- set first_user_message = messages[0]['content']|trim %}\n        {%- set messages = messages[1:] %}\n    {%- else %}\n        {{- raise_exception(\"Cannot put tools in the first user message when there's no first user message!\") }}\n{%- endif %}\n    {{- '<|start_header_id|>user<|end_header_id|>\\n\\n' -}}\n    {{- \"Given the following functions, please respond with a JSON for a function call \" }}\n    {{- \"with its proper arguments that best answers the given prompt.\\n\\n\" }}\n    {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n    {{- \"Do not use variables.\\n\\n\" }}\n    {%- for t in tools %}\n        {{- t | tojson(indent=4) }}\n        {{- \"\\n\\n\" }}\n    {%- endfor %}\n    {{- first_user_message + \"<|eot_id|>\"}}\n{%- endif %}\n\n{%- for message in messages %}\n    {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}\n        {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\\n\\n'+ message['content'] | trim + '<|eot_id|>' }}\n    {%- elif 'tool_calls' in message %}\n        {%- if not message.tool_calls|length == 1 %}\n            {{- raise_exception(\"This model only supports single tool-calls at once!\") }}\n        {%- endif %}\n        {%- set tool_call = message.tool_calls[0].function %}\n        {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n        {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n        {{- '\"parameters\": ' }}\n        {{- tool_call.arguments | tojson }}\n        {{- \"}\" }}\n        {{- \"<|eot_id|>\" }}\n    {%- elif message.role == \"tool\" or message.role == \"ipython\" %}\n        {{- \"<|start_header_id|>ipython<|end_header_id|>\\n\\n\" }}\n        {%- if message.content is mapping or message.content is iterable %}\n            {{- message.content | tojson }}\n        {%- else %}\n            {{- message.content }}\n        {%- endif %}\n        {{- \"<|eot_id|>\" }}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' }}\n{%- endif %}\n","bos_token":"<|begin_of_text|>","eos_token":"<|eot_id|>","build_info":"b5764-f667f1e6"}
request: {"messages":[{"role":"user","content":"hello"}],"stream":true,"cache_prompt":true,"samplers":"edkypmxt","temperature":0.8,"dynatemp_range":0,"dynatemp_exponent":1,"top_k":40,"top_p":0.95,"min_p":0.05,"typical_p":1,"xtc_probability":0,"xtc_threshold":0.1,"repeat_last_n":64,"repeat_penalty":1,"presence_penalty":0,"frequency_penalty":0,"dry_multiplier":0,"dry_base":1.75,"dry_allowed_length":2,"dry_penalty_last_n":-1,"max_tokens":-1,"timings_per_token":false}
srv  params_from_: Grammar: 
srv  params_from_: Grammar lazy: false
srv  params_from_: Chat format: Content-only
srv  add_waiting_: add task 0 to waiting list. current waiting = 0 (before add)
que          post: new task, id = 0/1, front = 0
que    start_loop: processing new tasks
que    start_loop: processing task, id = 0
slot get_availabl: id  0 | task -1 | selected slot by lru, t_last = -1
slot        reset: id  0 | task -1 | 
slot launch_slot_: id  0 | task 0 | launching slot : {"id":0,"id_task":0,"n_ctx":2048,"speculative":false,"is_processing":false,"params":{"n_predict":-1,"seed":4294967295,"temperature":0.800000011920929,"dynatemp_range":0.0,"dynatemp_exponent":1.0,"top_k":40,"top_p":0.949999988079071,"min_p":0.05000000074505806,"top_n_sigma":-1.0,"xtc_probability":0.0,"xtc_threshold":0.10000000149011612,"typical_p":1.0,"repeat_last_n":64,"repeat_penalty":1.0,"presence_penalty":0.0,"frequency_penalty":0.0,"dry_multiplier":0.0,"dry_base":1.75,"dry_allowed_length":2,"dry_penalty_last_n":2048,"dry_sequence_breakers":["\n",":","\"","*"],"mirostat":0,"mirostat_tau":5.0,"mirostat_eta":0.10000000149011612,"stop":[],"max_tokens":-1,"n_keep":0,"n_discard":0,"ignore_eos":false,"stream":true,"logit_bias":[],"n_probs":0,"min_keep":0,"grammar":"","grammar_lazy":false,"grammar_triggers":[],"preserved_tokens":[],"chat_format":"Content-only","reasoning_format":"deepseek","reasoning_in_content":false,"thinking_forced_open":false,"samplers":["penalties","dry","top_k","typ_p","top_p","min_p","xtc","temperature"],"speculative.n_max":16,"speculative.n_min":0,"speculative.p_min":0.75,"timings_per_token":false,"post_sampling_probs":false,"lora":[]},"prompt":"<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\nCutting Knowledge Date: December 2023\nToday Date: 25 Jul 2025\n\n<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nhello<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n","next_token":{"has_next_token":true,"has_new_line":false,"n_remain":-1,"n_decoded":0,"stopping_word":""}}
slot launch_slot_: id  0 | task 0 | processing task
que    start_loop: update slots
srv  update_slots: posting NEXT_RESPONSE
que          post: new task, id = 1, front = 0
slot update_slots: id  0 | task 0 | new prompt, n_ctx_slot = 2048, n_keep = 0, n_prompt_tokens = 36
slot update_slots: id  0 | task 0 | trying to reuse chunks with size > 256, slot.n_past = 0
slot update_slots: id  0 | task 0 | after context reuse, new slot.n_past = 0
slot update_slots: id  0 | task 0 | kv cache rm [0, end)
slot update_slots: id  0 | task 0 | prompt processing progress, n_past = 36, n_tokens = 36, progress = 1.000000
slot update_slots: id  0 | task 0 | prompt done, n_past = 36, n_tokens = 36
srv  update_slots: decoding batch, n_tokens = 36
clear_adapter_lora: call
set_embeddings: value = 0
ggml_cuda_compute_forward: RMS_NORM failed
/src/ramalama/llama.cpp/ggml/src/ggml-cuda/ggml-cuda.cu:78: ROCm errorROCm error: invalid device function
  current device: 0, in function ggml_cuda_compute_forward at /src/ramalama/llama.cpp/ggml/src/ggml-cuda/ggml-cuda.cu:2399
  err

/lib64/libggml-base.so(+0x2e65) [0x7f367aa53e65]
/lib64/libggml-base.so(ggml_print_backtrace+0x1ec) [0x7f367aa5422c]
/lib64/libggml-base.so(ggml_abort+0xd6) [0x7f367aa54356]
/lib64/libggml-hip.so(+0xdfe32) [0x7f367abdce32]
/lib64/libggml-hip.so(+0xe6769) [0x7f367abe3769]
/lib64/libggml-base.so(ggml_backend_sched_graph_compute_async+0x400) [0x7f367aa697b0]
/lib64/libllama.so(_ZN13llama_context13graph_computeEP11ggml_cgraphb+0x90) [0x7f36925684c0]
/lib64/libllama.so(_ZN13llama_context14process_ubatchERK12llama_ubatch14llm_graph_typeP22llama_memory_context_iR11ggml_status+0xe9) [0x7f3692568719]
/lib64/libllama.so(_ZN13llama_context6decodeERK11llama_batch+0x3b8) [0x7f369256d8b8]
/lib64/libllama.so(llama_decode+0xe) [0x7f369256e93e]
llama-server() [0x49b403]
llama-server() [0x46cdc9]
llama-server() [0x4314a2]
/lib64/libc.so.6(+0x35f5) [0x7f367a4d15f5]
/lib64/libc.so.6(__libc_start_main+0x88) [0x7f367a4d16a8]
llama-server() [0x433175]

- if tools is not none %}\n    {{- \"Environment: ipython\\n\" }}\n{%- endif %}\n{{- \"Cutting Knowledge Date: December 2023\\n\" }}\n{{- \"Today Date: \" + date_string + \"\\n\\n\" }}\n{%- if tools is not none and not tools_in_user_message %}\n    {{- \"You have access to the following functions. To call a function, please respond with JSON for a function call.\" }}\n    {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n    {{- \"Do not use variables.\\n\\n\" }}\n    {%- for t in tools %}\n        {{- t | tojson(indent=4) }}\n        {{- \"\\n\\n\" }}\n    {%- endfor %}\n{%- endif %}\n{{- system_message }}\n{{- \"<|eot_id|>\" }}\n\n{#- Custom tools are passed in a user message with some extra guidance #}\n{%- if tools_in_user_message and not tools is none %}\n    {#- Extract the first user message so we can plug it in here #}\n    {%- if messages | length != 0 %}\n        {%- set first_user_message = messages[0]['content']|trim %}\n        {%- set messages = messages[1:] %}\n    {%- else %}\n        {{- raise_exception(\"Cannot put tools in the first user message when there's no first user message!\") }}\n{%- endif %}\n    {{- '<|start_header_id|>user<|end_header_id|>\\n\\n' -}}\n    {{- \"Given the following functions, please respond with a JSON for a function call \" }}\n    {{- \"with its proper arguments that best answers the given prompt.\\n\\n\" }}\n    {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n    {{- \"Do not use variables.\\n\\n\" }}\n    {%- for t in tools %}\n        {{- t | tojson(indent=4) }}\n        {{- \"\\n\\n\" }}\n    {%- endfor %}\n    {{- first_user_message + \"<|eot_id|>\"}}\n{%- endif %}\n\n{%- for message in messages %}\n    {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}\n        {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\\n\\n'+ message['content'] | trim + '<|eot_id|>' }}\n    {%- elif 'tool_calls' in message %}\n        {%- if not message.tool_calls|length == 1 %}\n            {{- raise_exception(\"This model only supports single tool-calls at once!\") }}\n        {%- endif %}\n        {%- set tool_call = message.tool_calls[0].function %}\n        {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n        {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n        {{- '\"parameters\": ' }}\n        {{- tool_call.arguments | tojson }}\n        {{- \"}\" }}\n        {{- \"<|eot_id|>\" }}\n    {%- elif message.role == \"tool\" or message.role == \"ipython\" %}\n        {{- \"<|start_header_id|>ipython<|end_header_id|>\\n\\n\" }}\n        {%- if message.content is mapping or message.content is iterable %}\n            {{- message.content | tojson }}\n        {%- else %}\n            {{- message.content }}\n        {%- endif %}\n        {{- \"<|eot_id|>\" }}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' }}\n{%- endif %}\n","bos_token":"<|begin_of_text|>","eos_token":"<|eot_id|>","build_info":"b5764-f667f1e6"}
request: {"messages":[{"role":"user","content":"hello"}],"stream":true,"cache_prompt":true,"samplers":"edkypmxt","temperature":0.8,"dynatemp_range":0,"dynatemp_exponent":1,"top_k":40,"top_p":0.95,"min_p":0.05,"typical_p":1,"xtc_probability":0,"xtc_threshold":0.1,"repeat_last_n":64,"repeat_penalty":1,"presence_penalty":0,"frequency_penalty":0,"dry_multiplier":0,"dry_base":1.75,"dry_allowed_length":2,"dry_penalty_last_n":-1,"max_tokens":-1,"timings_per_token":false}
srv  params_from_: Grammar: 
srv  params_from_: Grammar lazy: false
srv  params_from_: Chat format: Content-only
srv  add_waiting_: add task 0 to waiting list. current waiting = 0 (before add)
que          post: new task, id = 0/1, front = 0
que    start_loop: processing new tasks
que    start_loop: processing task, id = 0
slot get_availabl: id  0 | task -1 | selected slot by lru, t_last = -1
slot        reset: id  0 | task -1 | 
slot launch_slot_: id  0 | task 0 | launching slot : {"id":0,"id_task":0,"n_ctx":2048,"speculative":false,"is_processing":false,"params":{"n_predict":-1,"seed":4294967295,"temperature":0.800000011920929,"dynatemp_range":0.0,"dynatemp_exponent":1.0,"top_k":40,"top_p":0.949999988079071,"min_p":0.05000000074505806,"top_n_sigma":-1.0,"xtc_probability":0.0,"xtc_threshold":0.10000000149011612,"typical_p":1.0,"repeat_last_n":64,"repeat_penalty":1.0,"presence_penalty":0.0,"frequency_penalty":0.0,"dry_multiplier":0.0,"dry_base":1.75,"dry_allowed_length":2,"dry_penalty_last_n":2048,"dry_sequence_breakers":["\n",":","\"","*"],"mirostat":0,"mirostat_tau":5.0,"mirostat_eta":0.10000000149011612,"stop":[],"max_tokens":-1,"n_keep":0,"n_discard":0,"ignore_eos":false,"stream":true,"logit_bias":[],"n_probs":0,"min_keep":0,"grammar":"","grammar_lazy":false,"grammar_triggers":[],"preserved_tokens":[],"chat_format":"Content-only","reasoning_format":"deepseek","reasoning_in_content":false,"thinking_forced_open":false,"samplers":["penalties","dry","top_k","typ_p","top_p","min_p","xtc","temperature"],"speculative.n_max":16,"speculative.n_min":0,"speculative.p_min":0.75,"timings_per_token":false,"post_sampling_probs":false,"lora":[]},"prompt":"<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\nCutting Knowledge Date: December 2023\nToday Date: 25 Jul 2025\n\n<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nhello<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n","next_token":{"has_next_token":true,"has_new_line":false,"n_remain":-1,"n_decoded":0,"stopping_word":""}}
slot launch_slot_: id  0 | task 0 | processing task
que    start_loop: update slots
srv  update_slots: posting NEXT_RESPONSE
que          post: new task, id = 1, front = 0
slot update_slots: id  0 | task 0 | new prompt, n_ctx_slot = 2048, n_keep = 0, n_prompt_tokens = 36
slot update_slots: id  0 | task 0 | trying to reuse chunks with size > 256, slot.n_past = 0
slot update_slots: id  0 | task 0 | after context reuse, new slot.n_past = 0
slot update_slots: id  0 | task 0 | kv cache rm [0, end)
slot update_slots: id  0 | task 0 | prompt processing progress, n_past = 36, n_tokens = 36, progress = 1.000000
slot update_slots: id  0 | task 0 | prompt done, n_past = 36, n_tokens = 36
srv  update_slots: decoding batch, n_tokens = 36
clear_adapter_lora: call
set_embeddings: value = 0
ggml_cuda_compute_forward: RMS_NORM failed
/src/ramalama/llama.cpp/ggml/src/ggml-cuda/ggml-cuda.cu:78: ROCm errorROCm error: invalid device function
  current device: 0, in function ggml_cuda_compute_forward at /src/ramalama/llama.cpp/ggml/src/ggml-cuda/ggml-cuda.cu:2399
  err

/lib64/libggml-base.so(+0x2e65) [0x7f367aa53e65]
/lib64/libggml-base.so(ggml_print_backtrace+0x1ec) [0x7f367aa5422c]
/lib64/libggml-base.so(ggml_abort+0xd6) [0x7f367aa54356]
/lib64/libggml-hip.so(+0xdfe32) [0x7f367abdce32]
/lib64/libggml-hip.so(+0xe6769) [0x7f367abe3769]
/lib64/libggml-base.so(ggml_backend_sched_graph_compute_async+0x400) [0x7f367aa697b0]
/lib64/libllama.so(_ZN13llama_context13graph_computeEP11ggml_cgraphb+0x90) [0x7f36925684c0]
/lib64/libllama.so(_ZN13llama_context14process_ubatchERK12llama_ubatch14llm_graph_typeP22llama_memory_context_iR11ggml_status+0xe9) [0x7f3692568719]
/lib64/libllama.so(_ZN13llama_context6decodeERK11llama_batch+0x3b8) [0x7f369256d8b8]
/lib64/libllama.so(llama_decode+0xe) [0x7f369256e93e]
llama-server() [0x49b403]
llama-server() [0x46cdc9]
llama-server() [0x4314a2]
/lib64/libc.so.6(+0x35f5) [0x7f367a4d15f5]
/lib64/libc.so.6(__libc_start_main+0x88) [0x7f367a4d16a8]
llama-server() [0x433175]


    {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' }}
{%- endif %}
, example_format: '<|start_header_id|>system<|end_header_id|>

Cutting Knowledge Date: December 2023
Today Date: 25 Jul 2025

You are a helpful assistant<|eot_id|><|start_header_id|>user<|end_header_id|>

Hello<|eot_id|><|start_header_id|>assistant<|end_header_id|>

Hi there<|eot_id|><|start_header_id|>user<|end_header_id|>

How are you?<|eot_id|><|start_header_id|>assistant<|end_header_id|>

'
main: server is listening on http://0.0.0.0:8080 - starting the main loop
que    start_loop: processing new tasks
que    start_loop: update slots
srv  update_slots: all slots are idle
srv  kv_cache_cle: clearing KV cache
que    start_loop: waiting for new tasks
srv  log_server_r: request: GET / 172.17.0.1 200
srv  log_server_r: request:  
srv  log_server_r: response: �
srv  log_server_r: request: GET /favicon.ico 172.17.0.1 404
srv  log_server_r: request:  
srv  log_server_r: response: {"error":{"code":404,"message":"File Not Found","type":"not_found_error"}}
srv  log_server_r: request: GET /props 172.17.0.1 200
srv  log_server_r: request:  
srv  log_server_r: response: {"default_generation_settings":{"id":0,"id_task":-1,"n_ctx":2048,"speculative":false,"is_processing":false,"params":{"n_predict":-1,"seed":4294967295,"temperature":0.800000011920929,"dynatemp_range":0.0,"dynatemp_exponent":1.0,"top_k":40,"top_p":0.949999988079071,"min_p":0.05000000074505806,"top_n_sigma":-1.0,"xtc_probability":0.0,"xtc_threshold":0.10000000149011612,"typical_p":1.0,"repeat_last_n":64,"repeat_penalty":1.0,"presence_penalty":0.0,"frequency_penalty":0.0,"dry_multiplier":0.0,"dry_base":1.75,"dry_allowed_length":2,"dry_penalty_last_n":2048,"dry_sequence_breakers":["\n",":","\"","*"],"mirostat":0,"mirostat_tau":5.0,"mirostat_eta":0.10000000149011612,"stop":[],"max_tokens":-1,"n_keep":0,"n_discard":0,"ignore_eos":false,"stream":true,"logit_bias":[],"n_probs":0,"min_keep":0,"grammar":"","grammar_lazy":false,"grammar_triggers":[],"preserved_tokens":[],"chat_format":"Content-only","reasoning_format":"none","reasoning_in_content":false,"thinking_forced_open":false,"samplers":["penalties","dry","top_n_sigma","top_k","typ_p","top_p","min_p","xtc","temperature"],"speculative.n_max":16,"speculative.n_min":0,"speculative.p_min":0.75,"timings_per_token":false,"post_sampling_probs":false,"lora":[]},"prompt":"","next_token":{"has_next_token":true,"has_new_line":false,"n_remain":-1,"n_decoded":0,"stopping_word":""}},"total_slots":1,"model_path":"/mnt/models/llama3.2","modalities":{"vision":false,"audio":false},"chat_template":"{{- bos_token }}\n{%- if custom_tools is defined %}\n    {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n    {%- set tools_in_user_message = true %}\n{%- endif %}\n{%- if not date_string is defined %}\n    {%- if strftime_now is defined %}\n        {%- set date_string = strftime_now(\"%d %b %Y\") %}\n    {%- else %}\n        {%- set date_string = \"26 Jul 2024\" %}\n    {%- endif %}\n{%- endif %}\n{%- if not tools is defined %}\n    {%- set tools = none %}\n{%- endif %}\n\n{#- This block extracts the system message, so we can slot it into the right place. #}\n{%- if messages[0]['role'] == 'system' %}\n    {%- set system_message = messages[0]['content']|trim %}\n    {%- set messages = messages[1:] %}\n{%- else %}\n    {%- set system_message = \"\" %}\n{%- endif %}\n\n{#- System message #}\n{{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n{%- if tools is not none %}\n    {{- \"Environment: ipython\\n\" }}\n{%- endif %}\n{{- \"Cutting Knowledge Date: December 2023\\n\" }}\n{{- \"Today Date: \" + date_string + \"\\n\\n\" }}\n{%- if tools is not none and not tools_in_user_message %}\n    {{- \"You have access to the following functions. To call a function, please respond with JSON for a function call.\" }}\n    {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n    {{- \"Do not use variables.\\n\\n\" }}\n    {%- for t in tools %}\n        {{- t | tojson(indent=4) }}\n        {{- \"\\n\\n\" }}\n    {%- endfor %}\n{%- endif %}\n{{- system_message }}\n{{- \"<|eot_id|>\" }}\n\n{#- Custom tools are passed in a user message with some extra guidance #}\n{%- if tools_in_user_message and not tools is none %}\n    {#- Extract the first user message so we can plug it in here #}\n    {%- if messages | length != 0 %}\n        {%- set first_user_message = messages[0]['content']|trim %}\n        {%- set messages = messages[1:] %}\n    {%- else %}\n        {{- raise_exception(\"Cannot put tools in the first user message when there's no first user message!\") }}\n{%- endif %}\n    {{- '<|start_header_id|>user<|end_header_id|>\\n\\n' -}}\n    {{- \"Given the following functions, please respond with a JSON for a function call \" }}\n    {{- \"with its proper arguments that best answers the given prompt.\\n\\n\" }}\n    {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n    {{- \"Do not use variables.\\n\\n\" }}\n    {%- for t in tools %}\n        {{- t | tojson(indent=4) }}\n        {{- \"\\n\\n\" }}\n    {%- endfor %}\n    {{- first_user_message + \"<|eot_id|>\"}}\n{%- endif %}\n\n{%- for message in messages %}\n    {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}\n        {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\\n\\n'+ message['content'] | trim + '<|eot_id|>' }}\n    {%- elif 'tool_calls' in message %}\n        {%- if not message.tool_calls|length == 1 %}\n            {{- raise_exception(\"This model only supports single tool-calls at once!\") }}\n        {%- endif %}\n        {%- set tool_call = message.tool_calls[0].function %}\n        {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n        {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n        {{- '\"parameters\": ' }}\n        {{- tool_call.arguments | tojson }}\n        {{- \"}\" }}\n        {{- \"<|eot_id|>\" }}\n    {%- elif message.role == \"tool\" or message.role == \"ipython\" %}\n        {{- \"<|start_header_id|>ipython<|end_header_id|>\\n\\n\" }}\n        {%- if message.content is mapping or message.content is iterable %}\n            {{- message.content | tojson }}\n        {%- else %}\n            {{- message.content }}\n        {%- endif %}\n        {{- \"<|eot_id|>\" }}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' }}\n{%- endif %}\n","bos_token":"<|begin_of_text|>","eos_token":"<|eot_id|>","build_info":"b5764-f667f1e6"}
request: {"messages":[{"role":"user","content":"hello"}],"stream":true,"cache_prompt":true,"samplers":"edkypmxt","temperature":0.8,"dynatemp_range":0,"dynatemp_exponent":1,"top_k":40,"top_p":0.95,"min_p":0.05,"typical_p":1,"xtc_probability":0,"xtc_threshold":0.1,"repeat_last_n":64,"repeat_penalty":1,"presence_penalty":0,"frequency_penalty":0,"dry_multiplier":0,"dry_base":1.75,"dry_allowed_length":2,"dry_penalty_last_n":-1,"max_tokens":-1,"timings_per_token":false}
srv  params_from_: Grammar: 
srv  params_from_: Grammar lazy: false
srv  params_from_: Chat format: Content-only
srv  add_waiting_: add task 0 to waiting list. current waiting = 0 (before add)
que          post: new task, id = 0/1, front = 0
que    start_loop: processing new tasks
que    start_loop: processing task, id = 0
slot get_availabl: id  0 | task -1 | selected slot by lru, t_last = -1
slot        reset: id  0 | task -1 | 
slot launch_slot_: id  0 | task 0 | launching slot : {"id":0,"id_task":0,"n_ctx":2048,"speculative":false,"is_processing":false,"params":{"n_predict":-1,"seed":4294967295,"temperature":0.800000011920929,"dynatemp_range":0.0,"dynatemp_exponent":1.0,"top_k":40,"top_p":0.949999988079071,"min_p":0.05000000074505806,"top_n_sigma":-1.0,"xtc_probability":0.0,"xtc_threshold":0.10000000149011612,"typical_p":1.0,"repeat_last_n":64,"repeat_penalty":1.0,"presence_penalty":0.0,"frequency_penalty":0.0,"dry_multiplier":0.0,"dry_base":1.75,"dry_allowed_length":2,"dry_penalty_last_n":2048,"dry_sequence_breakers":["\n",":","\"","*"],"mirostat":0,"mirostat_tau":5.0,"mirostat_eta":0.10000000149011612,"stop":[],"max_tokens":-1,"n_keep":0,"n_discard":0,"ignore_eos":false,"stream":true,"logit_bias":[],"n_probs":0,"min_keep":0,"grammar":"","grammar_lazy":false,"grammar_triggers":[],"preserved_tokens":[],"chat_format":"Content-only","reasoning_format":"deepseek","reasoning_in_content":false,"thinking_forced_open":false,"samplers":["penalties","dry","top_k","typ_p","top_p","min_p","xtc","temperature"],"speculative.n_max":16,"speculative.n_min":0,"speculative.p_min":0.75,"timings_per_token":false,"post_sampling_probs":false,"lora":[]},"prompt":"<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\nCutting Knowledge Date: December 2023\nToday Date: 25 Jul 2025\n\n<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nhello<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n","next_token":{"has_next_token":true,"has_new_line":false,"n_remain":-1,"n_decoded":0,"stopping_word":""}}
slot launch_slot_: id  0 | task 0 | processing task
que    start_loop: update slots
srv  update_slots: posting NEXT_RESPONSE
que          post: new task, id = 1, front = 0
slot update_slots: id  0 | task 0 | new prompt, n_ctx_slot = 2048, n_keep = 0, n_prompt_tokens = 36
slot update_slots: id  0 | task 0 | trying to reuse chunks with size > 256, slot.n_past = 0
slot update_slots: id  0 | task 0 | after context reuse, new slot.n_past = 0
slot update_slots: id  0 | task 0 | kv cache rm [0, end)
slot update_slots: id  0 | task 0 | prompt processing progress, n_past = 36, n_tokens = 36, progress = 1.000000
slot update_slots: id  0 | task 0 | prompt done, n_past = 36, n_tokens = 36
srv  update_slots: decoding batch, n_tokens = 36
clear_adapter_lora: call
set_embeddings: value = 0
ggml_cuda_compute_forward: RMS_NORM failed
/src/ramalama/llama.cpp/ggml/src/ggml-cuda/ggml-cuda.cu:78: ROCm errorROCm error: invalid device function
  current device: 0, in function ggml_cuda_compute_forward at /src/ramalama/llama.cpp/ggml/src/ggml-cuda/ggml-cuda.cu:2399
  err

/lib64/libggml-base.so(+0x2e65) [0x7f367aa53e65]
/lib64/libggml-base.so(ggml_print_backtrace+0x1ec) [0x7f367aa5422c]
/lib64/libggml-base.so(ggml_abort+0xd6) [0x7f367aa54356]
/lib64/libggml-hip.so(+0xdfe32) [0x7f367abdce32]
/lib64/libggml-hip.so(+0xe6769) [0x7f367abe3769]
/lib64/libggml-base.so(ggml_backend_sched_graph_compute_async+0x400) [0x7f367aa697b0]
/lib64/libllama.so(_ZN13llama_context13graph_computeEP11ggml_cgraphb+0x90) [0x7f36925684c0]
/lib64/libllama.so(_ZN13llama_context14process_ubatchERK12llama_ubatch14llm_graph_typeP22llama_memory_context_iR11ggml_status+0xe9) [0x7f3692568719]
/lib64/libllama.so(_ZN13llama_context6decodeERK11llama_batch+0x3b8) [0x7f369256d8b8]
/lib64/libllama.so(llama_decode+0xe) [0x7f369256e93e]
llama-server() [0x49b403]
llama-server() [0x46cdc9]
llama-server() [0x4314a2]
/lib64/libc.so.6(+0x35f5) [0x7f367a4d15f5]
/lib64/libc.so.6(__libc_start_main+0x88) [0x7f367a4d16a8]
llama-server() [0x433175]

[CsBigDataHub]

adding issue from other project for tracking

containers/ramalama#1705

[CsBigDataHub]

rocminfo

�[37mROCk module is loaded�[0m
=====================    
HSA System Attributes    
=====================    
Runtime Version:         1.15
Runtime Ext Version:     1.7
System Timestamp Freq.:  1000.000000MHz
Sig. Max Wait Duration:  18446744073709551615 (0xFFFFFFFFFFFFFFFF) (timestamp count)
Machine Model:           LARGE                              
System Endianness:       LITTLE                             
Mwaitx:                  DISABLED
XNACK enabled:           NO
DMAbuf Support:          YES
VMM Support:             YES

==========               
HSA Agents               
==========               
*******                  
Agent 1                  
*******                  
  Name:                    AMD Ryzen 9 7900X3D 12-Core Processor
  Uuid:                    CPU-XX                             
  Marketing Name:          AMD Ryzen 9 7900X3D 12-Core Processor
  Vendor Name:             CPU                                
  Feature:                 None specified                     
  Profile:                 FULL_PROFILE                       
  Float Round Mode:        NEAR                               
  Max Queue Number:        0(0x0)                             
  Queue Min Size:          0(0x0)                             
  Queue Max Size:          0(0x0)                             
  Queue Type:              MULTI                              
  Node:                    0                                  
  Device Type:             CPU                                
  Cache Info:              
    L1:                      32768(0x8000) KB                   
  Chip ID:                 0(0x0)                             
  ASIC Revision:           0(0x0)                             
  Cacheline Size:          64(0x40)                           
  Max Clock Freq. (MHz):   5663                               
  BDFID:                   0                                  
  Internal Node ID:        0                                  
  Compute Unit:            24                                 
  SIMDs per CU:            0                                  
  Shader Engines:          0                                  
  Shader Arrs. per Eng.:   0                                  
  WatchPts on Addr. Ranges:1                                  
  Memory Properties:       
  Features:                None
  Pool Info:               
    Pool 1                   
      Segment:                 GLOBAL; FLAGS: FINE GRAINED        
      Size:                    64906008(0x3de6318) KB             
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Recommended Granule:4KB                                
      Alloc Alignment:         4KB                                
      Accessible by all:       TRUE                               
    Pool 2                   
      Segment:                 GLOBAL; FLAGS: EXTENDED FINE GRAINED
      Size:                    64906008(0x3de6318) KB             
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Recommended Granule:4KB                                
      Alloc Alignment:         4KB                                
      Accessible by all:       TRUE                               
    Pool 3                   
      Segment:                 GLOBAL; FLAGS: KERNARG, FINE GRAINED
      Size:                    64906008(0x3de6318) KB             
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Recommended Granule:4KB                                
      Alloc Alignment:         4KB                                
      Accessible by all:       TRUE                               
    Pool 4                   
      Segment:                 GLOBAL; FLAGS: COARSE GRAINED      
      Size:                    64906008(0x3de6318) KB             
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Recommended Granule:4KB                                
      Alloc Alignment:         4KB                                
      Accessible by all:       TRUE                               
  ISA Info:                
*******                  
Agent 2                  
*******                  
  Name:                    gfx1030                            
  Uuid:                    GPU-05adfed9533c4b2a               
  Marketing Name:          AMD Radeon RX 6800                 
  Vendor Name:             AMD                                
  Feature:                 KERNEL_DISPATCH                    
  Profile:                 BASE_PROFILE                       
  Float Round Mode:        NEAR                               
  Max Queue Number:        128(0x80)                          
  Queue Min Size:          64(0x40)                           
  Queue Max Size:          131072(0x20000)                    
  Queue Type:              MULTI                              
  Node:                    1                                  
  Device Type:             GPU                                
  Cache Info:              
    L1:                      16(0x10) KB                        
    L2:                      4096(0x1000) KB                    
    L3:                      131072(0x20000) KB                 
  Chip ID:                 29631(0x73bf)                      
  ASIC Revision:           1(0x1)                             
  Cacheline Size:          128(0x80)                          
  Max Clock Freq. (MHz):   2475                               
  BDFID:                   768                                
  Internal Node ID:        1                                  
  Compute Unit:            60                                 
  SIMDs per CU:            2                                  
  Shader Engines:          4                                  
  Shader Arrs. per Eng.:   2                                  
  WatchPts on Addr. Ranges:4                                  
  Coherent Host Access:    FALSE                              
  Memory Properties:       
  Features:                KERNEL_DISPATCH 
  Fast F16 Operation:      TRUE                               
  Wavefront Size:          32(0x20)                           
  Workgroup Max Size:      1024(0x400)                        
  Workgroup Max Size per Dimension:
    x                        1024(0x400)                        
    y                        1024(0x400)                        
    z                        1024(0x400)                        
  Max Waves Per CU:        32(0x20)                           
  Max Work-item Per CU:    1024(0x400)                        
  Grid Max Size:           4294967295(0xffffffff)             
  Grid Max Size per Dimension:
    x                        4294967295(0xffffffff)             
    y                        4294967295(0xffffffff)             
    z                        4294967295(0xffffffff)             
  Max fbarriers/Workgrp:   32                                 
  Packet Processor uCode:: 131                                
  SDMA engine uCode::      85                                 
  IOMMU Support::          None                               
  Pool Info:               
    Pool 1                   
      Segment:                 GLOBAL; FLAGS: COARSE GRAINED      
      Size:                    16760832(0xffc000) KB              
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Recommended Granule:2048KB                             
      Alloc Alignment:         4KB                                
      Accessible by all:       FALSE                              
    Pool 2                   
      Segment:                 GLOBAL; FLAGS: EXTENDED FINE GRAINED
      Size:                    16760832(0xffc000) KB              
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Recommended Granule:2048KB                             
      Alloc Alignment:         4KB                                
      Accessible by all:       FALSE                              
    Pool 3                   
      Segment:                 GROUP                              
      Size:                    64(0x40) KB                        
      Allocatable:             FALSE                              
      Alloc Granule:           0KB                                
      Alloc Recommended Granule:0KB                                
      Alloc Alignment:         0KB                                
      Accessible by all:       FALSE                              
  ISA Info:                
    ISA 1                    
      Name:                    amdgcn-amd-amdhsa--gfx1030         
      Machine Models:          HSA_MACHINE_MODEL_LARGE            
      Profiles:                HSA_PROFILE_BASE                   
      Default Rounding Mode:   NEAR                               
      Default Rounding Mode:   NEAR                               
      Fast f16:                TRUE                               
      Workgroup Max Size:      1024(0x400)                        
      Workgroup Max Size per Dimension:
        x                        1024(0x400)                        
        y                        1024(0x400)                        
        z                        1024(0x400)                        
      Grid Max Size:           4294967295(0xffffffff)             
      Grid Max Size per Dimension:
        x                        4294967295(0xffffffff)             
        y                        4294967295(0xffffffff)             
        z                        4294967295(0xffffffff)             
      FBarrier Max Size:       32                                 
    ISA 2                    
      Name:                    amdgcn-amd-amdhsa--gfx10-3-generic 
      Machine Models:          HSA_MACHINE_MODEL_LARGE            
      Profiles:                HSA_PROFILE_BASE                   
      Default Rounding Mode:   NEAR                               
      Default Rounding Mode:   NEAR                               
      Fast f16:                TRUE                               
      Workgroup Max Size:      1024(0x400)                        
      Workgroup Max Size per Dimension:
        x                        1024(0x400)                        
        y                        1024(0x400)                        
        z                        1024(0x400)                        
      Grid Max Size:           4294967295(0xffffffff)             
      Grid Max Size per Dimension:
        x                        4294967295(0xffffffff)             
        y                        4294967295(0xffffffff)             
        z                        4294967295(0xffffffff)             
      FBarrier Max Size:       32                                 
*******                  
Agent 3                  
*******                  
  Name:                    gfx1036                            
  Uuid:                    GPU-XX                             
  Marketing Name:          AMD Radeon Graphics                
  Vendor Name:             AMD                                
  Feature:                 KERNEL_DISPATCH                    
  Profile:                 BASE_PROFILE                       
  Float Round Mode:        NEAR                               
  Max Queue Number:        128(0x80)                          
  Queue Min Size:          64(0x40)                           
  Queue Max Size:          131072(0x20000)                    
  Queue Type:              MULTI                              
  Node:                    2                                  
  Device Type:             GPU                                
  Cache Info:              
    L1:                      16(0x10) KB                        
    L2:                      256(0x100) KB                      
  Chip ID:                 5710(0x164e)                       
  ASIC Revision:           1(0x1)                             
  Cacheline Size:          128(0x80)                          
  Max Clock Freq. (MHz):   2200                               
  BDFID:                   6144                               
  Internal Node ID:        2                                  
  Compute Unit:            2                                  
  SIMDs per CU:            2                                  
  Shader Engines:          1                                  
  Shader Arrs. per Eng.:   1                                  
  WatchPts on Addr. Ranges:4                                  
  Coherent Host Access:    FALSE                              
  Memory Properties:       APU
  Features:                KERNEL_DISPATCH 
  Fast F16 Operation:      TRUE                               
  Wavefront Size:          32(0x20)                           
  Workgroup Max Size:      1024(0x400)                        
  Workgroup Max Size per Dimension:
    x                        1024(0x400)                        
    y                        1024(0x400)                        
    z                        1024(0x400)                        
  Max Waves Per CU:        32(0x20)                           
  Max Work-item Per CU:    1024(0x400)                        
  Grid Max Size:           4294967295(0xffffffff)             
  Grid Max Size per Dimension:
    x                        4294967295(0xffffffff)             
    y                        4294967295(0xffffffff)             
    z                        4294967295(0xffffffff)             
  Max fbarriers/Workgrp:   32                                 
  Packet Processor uCode:: 22                                 
  SDMA engine uCode::      9                                  
  IOMMU Support::          None                               
  Pool Info:               
    Pool 1                   
      Segment:                 GLOBAL; FLAGS: COARSE GRAINED      
      Size:                    32453004(0x1ef318c) KB             
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Recommended Granule:2048KB                             
      Alloc Alignment:         4KB                                
      Accessible by all:       FALSE                              
    Pool 2                   
      Segment:                 GLOBAL; FLAGS: EXTENDED FINE GRAINED
      Size:                    32453004(0x1ef318c) KB             
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Recommended Granule:2048KB                             
      Alloc Alignment:         4KB                                
      Accessible by all:       FALSE                              
    Pool 3                   
      Segment:                 GROUP                              
      Size:                    64(0x40) KB                        
      Allocatable:             FALSE                              
      Alloc Granule:           0KB                                
      Alloc Recommended Granule:0KB                                
      Alloc Alignment:         0KB                                
      Accessible by all:       FALSE                              
  ISA Info:                
    ISA 1                    
      Name:                    amdgcn-amd-amdhsa--gfx1036         
      Machine Models:          HSA_MACHINE_MODEL_LARGE            
      Profiles:                HSA_PROFILE_BASE                   
      Default Rounding Mode:   NEAR                               
      Default Rounding Mode:   NEAR                               
      Fast f16:                TRUE                               
      Workgroup Max Size:      1024(0x400)                        
      Workgroup Max Size per Dimension:
        x                        1024(0x400)                        
        y                        1024(0x400)                        
        z                        1024(0x400)                        
      Grid Max Size:           4294967295(0xffffffff)             
      Grid Max Size per Dimension:
        x                        4294967295(0xffffffff)             
        y                        4294967295(0xffffffff)             
        z                        4294967295(0xffffffff)             
      FBarrier Max Size:       32                                 
    ISA 2                    /opt/rocm
      Name:                    amdgcn-amd-amdhsa--gfx10-3-generic 
      Machine Models:          HSA_MACHINE_MODEL_LARGE            
      Profiles:                HSA_PROFILE_BASE                   
      Default Rounding Mode:   NEAR                               
      Default Rounding Mode:   NEAR                               
      Fast f16:                TRUE                               
      Workgroup Max Size:      1024(0x400)                        
      Workgroup Max Size per Dimension:
        x                        1024(0x400)                        
        y                        1024(0x400)                        
        z                        1024(0x400)                        
      Grid Max Size:           4294967295(0xffffffff)             
      Grid Max Size per Dimension:
        x                        4294967295(0xffffffff)             
        y                        4294967295(0xffffffff)             
        z                        4294967295(0xffffffff)             
      FBarrier Max Size:       32                                 
*** Done ***             

[CsBigDataHub]

Just posting the command here

docker run --rm --label ai.ramalama.model=llama3.2:3b \
--label ai.ramalama.engine=docker --label ai.ramalama.runtime=llama.cpp \
--label ai.ramalama.port=8080 --label ai.ramalama.command=run --device /dev/dri --device /dev/kfd \
-e HIP_VISIBLE_DEVICES=1 -p 8080:8080 --security-opt=label=disable \
--cap-drop=all --security-opt=no-new-privileges -t -i --label ai.ramalama \
--name ramalama_IGngq1HF2u --env=HOME=/tmp --init \
--mount=type=bind,src=/home/mypc/.local/share/ramalama/store/ollama/library/llama3.2/blobs/sha256-dde5aa3fc5ffc17176b5e8bdc82f587b24b2678c6c66101bf7da77af9f7ccdff,destination=/mnt/models/llama3.2,ro --mount=type=bind,src=/home/mypc/.local/share/ramalama/store/ollama/library/llama3.2/blobs/sha256-34bb5ab01051a11372a91f95f3fbbc51173eed8e7f13ec395b9ae9b8bd0e242b,destination=/mnt/models/config.json,ro \
--mount=type=bind,src=/home/mypc/.local/share/ramalama/store/ollama/library/llama3.2/blobs/sha256-966de95ca8a62200913e3f8bfbf84c8494536f1b94b49166851e76644e966396,destination=/mnt/models/chat_template,ro \
quay.io/ramalama/rocm:latest llama-server --port 8080 \
--model /mnt/models/llama3.2 --no-warmup --jinja --log-colors --alias llama3.2:3b \
--ctx-size 2048 --temp 0.8 --cache-reuse 256 -v -ngl 999 --threads 12 --host 0.0.0.0 

HIP_VISIBLE_DEVICES=2 is what I used to offload to CPU and that works.

HIP_VISIBLE_DEVICES=1 crashes llama.cpp

[CsBigDataHub]

@chowdri In my case setting HIP_VISIBLE_DEVICES=0 is offloading to GPU.

[chowdri]

I tried using this environment variable:

$ export HIP_VISIBLE_DEVICES=0

$ llama-bench -m .lmstudio/models/lmstudio-community/Qwen3-14B-GGUF/Qwen3-14B-Q8_0.gguf 
ggml_cuda_init: GGML_CUDA_FORCE_MMQ:    no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 1 ROCm devices:
  Device 0: Radeon RX 7900 GRE, gfx1100 (0x1100), VMM: no, Wave Size: 32
| model                          |       size |     params | backend    | ngl |            test |                  t/s |
| ------------------------------ | ---------: | ---------: | ---------- | --: | --------------: | -------------------: |
| qwen3 14B Q8_0                 |  14.61 GiB |    14.77 B | ROCm       |  99 |           pp512 |       1051.76 ± 3.47 |
| qwen3 14B Q8_0                 |  14.61 GiB |    14.77 B | ROCm       |  99 |           tg128 |         29.21 ± 0.01 |

build: cbc68be5 (5898)

llama-cli -m .lmstudio/models/lmstudio-community/Qwen3-14B-GGUF/Qwen3-14B-Q8_0.gguf 
ggml_cuda_init: GGML_CUDA_FORCE_MMQ:    no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 1 ROCm devices:
  Device 0: Radeon RX 7900 GRE, gfx1100 (0x1100), VMM: no, Wave Size: 32
build: 5898 (cbc68be5) with cc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0 for x86_64-linux-gnu
main: llama backend init
main: load the model and apply lora adapter, if any
llama_model_load_from_file_impl: using device ROCm0 (Radeon RX 7900 GRE) - 16312 MiB free
llama_model_loader: loaded meta data with 27 key-value pairs and 443 tensors from .lmstudio/models/lmstudio-community/Qwen3-14B-GGUF/Qwen3-14B-Q8_0.gguf (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv   0:                       general.architecture str              = qwen3
llama_model_loader: - kv   1:                               general.type str              = model
llama_model_loader: - kv   2:                               general.name str              = Qwen3 14B
llama_model_loader: - kv   3:                           general.basename str              = Qwen3
llama_model_loader: - kv   4:                         general.size_label str              = 14B
llama_model_loader: - kv   5:                          qwen3.block_count u32              = 40
llama_model_loader: - kv   6:                       qwen3.context_length u32              = 32768
llama_model_loader: - kv   7:                     qwen3.embedding_length u32              = 5120
llama_model_loader: - kv   8:                  qwen3.feed_forward_length u32              = 17408
llama_model_loader: - kv   9:                 qwen3.attention.head_count u32              = 40
llama_model_loader: - kv  10:              qwen3.attention.head_count_kv u32              = 8
llama_model_loader: - kv  11:                       qwen3.rope.freq_base f32              = 1000000.000000
llama_model_loader: - kv  12:     qwen3.attention.layer_norm_rms_epsilon f32              = 0.000001
llama_model_loader: - kv  13:                 qwen3.attention.key_length u32              = 128
llama_model_loader: - kv  14:               qwen3.attention.value_length u32              = 128
llama_model_loader: - kv  15:                       tokenizer.ggml.model str              = gpt2
llama_model_loader: - kv  16:                         tokenizer.ggml.pre str              = qwen2
llama_model_loader: - kv  17:                      tokenizer.ggml.tokens arr[str,151936]  = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv  18:                  tokenizer.ggml.token_type arr[i32,151936]  = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv  19:                      tokenizer.ggml.merges arr[str,151387]  = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
llama_model_loader: - kv  20:                tokenizer.ggml.eos_token_id u32              = 151645
llama_model_loader: - kv  21:            tokenizer.ggml.padding_token_id u32              = 151643
llama_model_loader: - kv  22:                tokenizer.ggml.bos_token_id u32              = 151643
llama_model_loader: - kv  23:               tokenizer.ggml.add_bos_token bool             = false
llama_model_loader: - kv  24:                    tokenizer.chat_template str              = {%- if tools %}\n    {{- '<|im_start|>...
llama_model_loader: - kv  25:               general.quantization_version u32              = 2
llama_model_loader: - kv  26:                          general.file_type u32              = 7
llama_model_loader: - type  f32:  161 tensors
llama_model_loader: - type q8_0:  282 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type   = Q8_0
print_info: file size   = 14.61 GiB (8.50 BPW) 
load: special tokens cache size = 26
load: token to piece cache size = 0.9311 MB
print_info: arch             = qwen3
print_info: vocab_only       = 0
print_info: n_ctx_train      = 32768
print_info: n_embd           = 5120
print_info: n_layer          = 40
print_info: n_head           = 40
print_info: n_head_kv        = 8
print_info: n_rot            = 128
print_info: n_swa            = 0
print_info: is_swa_any       = 0
print_info: n_embd_head_k    = 128
print_info: n_embd_head_v    = 128
print_info: n_gqa            = 5
print_info: n_embd_k_gqa     = 1024
print_info: n_embd_v_gqa     = 1024
print_info: f_norm_eps       = 0.0e+00
print_info: f_norm_rms_eps   = 1.0e-06
print_info: f_clamp_kqv      = 0.0e+00
print_info: f_max_alibi_bias = 0.0e+00
print_info: f_logit_scale    = 0.0e+00
print_info: f_attn_scale     = 0.0e+00
print_info: n_ff             = 17408
print_info: n_expert         = 0
print_info: n_expert_used    = 0
print_info: causal attn      = 1
print_info: pooling type     = 0
print_info: rope type        = 2
print_info: rope scaling     = linear
print_info: freq_base_train  = 1000000.0
print_info: freq_scale_train = 1
print_info: n_ctx_orig_yarn  = 32768
print_info: rope_finetuned   = unknown
print_info: model type       = 14B
print_info: model params     = 14.77 B
print_info: general.name     = Qwen3 14B
print_info: vocab type       = BPE
print_info: n_vocab          = 151936
print_info: n_merges         = 151387
print_info: BOS token        = 151643 '<|endoftext|>'
print_info: EOS token        = 151645 '<|im_end|>'
print_info: EOT token        = 151645 '<|im_end|>'
print_info: PAD token        = 151643 '<|endoftext|>'
print_info: LF token         = 198 'Ċ'
print_info: FIM PRE token    = 151659 '<|fim_prefix|>'
print_info: FIM SUF token    = 151661 '<|fim_suffix|>'
print_info: FIM MID token    = 151660 '<|fim_middle|>'
print_info: FIM PAD token    = 151662 '<|fim_pad|>'
print_info: FIM REP token    = 151663 '<|repo_name|>'
print_info: FIM SEP token    = 151664 '<|file_sep|>'
print_info: EOG token        = 151643 '<|endoftext|>'
print_info: EOG token        = 151645 '<|im_end|>'
print_info: EOG token        = 151662 '<|fim_pad|>'
print_info: EOG token        = 151663 '<|repo_name|>'
print_info: EOG token        = 151664 '<|file_sep|>'
print_info: max token length = 256
load_tensors: loading model tensors, this can take a while... (mmap = true)
load_tensors: offloading 0 repeating layers to GPU
load_tensors: offloaded 0/41 layers to GPU
load_tensors:   CPU_Mapped model buffer size = 14965.61 MiB
............................................................................................
llama_context: constructing llama_context
llama_context: n_seq_max     = 1
llama_context: n_ctx         = 4096
llama_context: n_ctx_per_seq = 4096
llama_context: n_batch       = 2048
llama_context: n_ubatch      = 512
llama_context: causal_attn   = 1
llama_context: flash_attn    = 0
llama_context: freq_base     = 1000000.0
llama_context: freq_scale    = 1
llama_context: n_ctx_per_seq (4096) < n_ctx_train (32768) -- the full capacity of the model will not be utilized
llama_context:        CPU  output buffer size =     0.58 MiB
llama_kv_cache_unified:        CPU KV buffer size =   640.00 MiB
llama_kv_cache_unified: size =  640.00 MiB (  4096 cells,  40 layers,  1 seqs), K (f16):  320.00 MiB, V (f16):  320.00 MiB
llama_kv_cache_unified: LLAMA_SET_ROWS=0, using old ggml_cpy() method for backwards compatibility
llama_context:      ROCm0 compute buffer size =  1094.99 MiB
llama_context:  ROCm_Host compute buffer size =    18.01 MiB
llama_context: graph nodes  = 1606
llama_context: graph splits = 524 (with bs=512), 121 (with bs=1)
common_init_from_params: setting dry_penalty_last_n to ctx_size = 4096
common_init_from_params: warming up the model with an empty run - please wait ... (--no-warmup to disable)
main: llama threadpool init, n_threads = 16
main: chat template is available, enabling conversation mode (disable it with -no-cnv)
main: chat template example:
<|im_start|>system
You are a helpful assistant<|im_end|>
<|im_start|>user
Hello<|im_end|>
<|im_start|>assistant
Hi there<|im_end|>
<|im_start|>user
How are you?<|im_end|>
<|im_start|>assistant


system_info: n_threads = 16 (n_threads_batch = 16) / 32 | ROCm : NO_VMM = 1 | PEER_MAX_BATCH_SIZE = 128 | CPU : SSE3 = 1 | SSSE3 = 1 | AVX = 1 | AVX2 = 1 | F16C = 1 | FMA = 1 | BMI2 = 1 | AVX512 = 1 | AVX512_VBMI = 1 | AVX512_VNNI = 1 | AVX512_BF16 = 1 | LLAMAFILE = 1 | OPENMP = 1 | REPACK = 1 | 

main: interactive mode on.
sampler seed: 2541227824
sampler params: 
	repeat_last_n = 64, repeat_penalty = 1.000, frequency_penalty = 0.000, presence_penalty = 0.000
	dry_multiplier = 0.000, dry_base = 1.750, dry_allowed_length = 2, dry_penalty_last_n = 4096
	top_k = 40, top_p = 0.950, min_p = 0.050, xtc_probability = 0.000, xtc_threshold = 0.100, typical_p = 1.000, top_n_sigma = -1.000, temp = 0.800
	mirostat = 0, mirostat_lr = 0.100, mirostat_ent = 5.000
sampler chain: logits -> logit-bias -> penalties -> dry -> top-n-sigma -> top-k -> typical -> top-p -> min-p -> xtc -> temp-ext -> dist 
generate: n_ctx = 4096, n_batch = 2048, n_predict = -1, n_keep = 0

== Running in interactive mode. ==
 - Press Ctrl+C to interject at any time.
 - Press Return to return control to the AI.
 - To return control without starting a new line, end your input with '/'.
 - If you want to submit another line, end your input with '\'.
 - Not using system message. To change it, set a different value via -sys PROMPT


> 

The outcome is the same, the model runs on cpu.

Using HIP_VISIBLE_DEVICES=1, selects gfx900 and HIP_VISIBLE_DEVICES=2 selects cpu execution also.

rocminfo output:

$ rocminfo

ROCk module version 6.12.12 is loaded
=====================    
HSA System Attributes    
=====================    
Runtime Version:         1.15
Runtime Ext Version:     1.7
System Timestamp Freq.:  1000.000000MHz
Sig. Max Wait Duration:  18446744073709551615 (0xFFFFFFFFFFFFFFFF) (timestamp count)
Machine Model:           LARGE                              
System Endianness:       LITTLE                             
Mwaitx:                  DISABLED
XNACK enabled:           NO
DMAbuf Support:          YES
VMM Support:             YES

==========               
HSA Agents               
==========               
*******                  
Agent 1                  
*******                  
  Name:                    AMD Ryzen 9 7950X3D 16-Core Processor
  Uuid:                    CPU-XX                             
  Marketing Name:          AMD Ryzen 9 7950X3D 16-Core Processor
  Vendor Name:             CPU                                
  Feature:                 None specified                     
  Profile:                 FULL_PROFILE                       
  Float Round Mode:        NEAR                               
  Max Queue Number:        0(0x0)                             
  Queue Min Size:          0(0x0)                             
  Queue Max Size:          0(0x0)                             
  Queue Type:              MULTI                              
  Node:                    0                                  
  Device Type:             CPU                                
  Cache Info:              
    L1:                      32768(0x8000) KB                   
  Chip ID:                 0(0x0)                             
  ASIC Revision:           0(0x0)                             
  Cacheline Size:          64(0x40)                           
  Max Clock Freq. (MHz):   5763                               
  BDFID:                   0                                  
  Internal Node ID:        0                                  
  Compute Unit:            32                                 
  SIMDs per CU:            0                                  
  Shader Engines:          0                                  
  Shader Arrs. per Eng.:   0                                  
  WatchPts on Addr. Ranges:1                                  
  Memory Properties:       
  Features:                None
  Pool Info:               
    Pool 1                   
      Segment:                 GLOBAL; FLAGS: FINE GRAINED        
      Size:                    65427016(0x3e65648) KB             
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Recommended Granule:4KB                                
      Alloc Alignment:         4KB                                
      Accessible by all:       TRUE                               
    Pool 2                   
      Segment:                 GLOBAL; FLAGS: EXTENDED FINE GRAINED
      Size:                    65427016(0x3e65648) KB             
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Recommended Granule:4KB                                
      Alloc Alignment:         4KB                                
      Accessible by all:       TRUE                               
    Pool 3                   
      Segment:                 GLOBAL; FLAGS: KERNARG, FINE GRAINED
      Size:                    65427016(0x3e65648) KB             
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Recommended Granule:4KB                                
      Alloc Alignment:         4KB                                
      Accessible by all:       TRUE                               
    Pool 4                   
      Segment:                 GLOBAL; FLAGS: COARSE GRAINED      
      Size:                    65427016(0x3e65648) KB             
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Recommended Granule:4KB                                
      Alloc Alignment:         4KB                                
      Accessible by all:       TRUE                               
  ISA Info:                
*******                  
Agent 2                  
*******                  
  Name:                    gfx1100                            
  Uuid:                    GPU-fd9ca3bcfec72db2               
  Marketing Name:          Radeon RX 7900 GRE                 
  Vendor Name:             AMD                                
  Feature:                 KERNEL_DISPATCH                    
  Profile:                 BASE_PROFILE                       
  Float Round Mode:        NEAR                               
  Max Queue Number:        128(0x80)                          
  Queue Min Size:          64(0x40)                           
  Queue Max Size:          131072(0x20000)                    
  Queue Type:              MULTI                              
  Node:                    1                                  
  Device Type:             GPU                                
  Cache Info:              
    L1:                      32(0x20) KB                        
    L2:                      6144(0x1800) KB                    
    L3:                      65536(0x10000) KB                  
  Chip ID:                 29772(0x744c)                      
  ASIC Revision:           0(0x0)                             
  Cacheline Size:          128(0x80)                          
  Max Clock Freq. (MHz):   1927                               
  BDFID:                   768                                
  Internal Node ID:        1                                  
  Compute Unit:            80                                 
  SIMDs per CU:            2                                  
  Shader Engines:          6                                  
  Shader Arrs. per Eng.:   2                                  
  WatchPts on Addr. Ranges:4                                  
  Coherent Host Access:    FALSE                              
  Memory Properties:       
  Features:                KERNEL_DISPATCH 
  Fast F16 Operation:      TRUE                               
  Wavefront Size:          32(0x20)                           
  Workgroup Max Size:      1024(0x400)                        
  Workgroup Max Size per Dimension:
    x                        1024(0x400)                        
    y                        1024(0x400)                        
    z                        1024(0x400)                        
  Max Waves Per CU:        32(0x20)                           
  Max Work-item Per CU:    1024(0x400)                        
  Grid Max Size:           4294967295(0xffffffff)             
  Grid Max Size per Dimension:
    x                        4294967295(0xffffffff)             
    y                        4294967295(0xffffffff)             
    z                        4294967295(0xffffffff)             
  Max frocminfo
ROCk module version 6.12.12 is loaded
=====================    
HSA System Attributes    
=====================    
Runtime Version:         1.15
Runtime Ext Version:     1.7
System Timestamp Freq.:  1000.000000MHz
Sig. Max Wait Duration:  18446744073709551615 (0xFFFFFFFFFFFFFFFF) (timestamp count)
Machine Model:           LARGE                              
System Endianness:       LITTLE                             
Mwaitx:                  DISABLED
XNACK enabled:           NO
DMAbuf Support:          YES
VMM Support:             YES

==========               
HSA Agents               
==========               
*******                  
Agent 1                  
*******                  
  Name:                    AMD Ryzen 9 7950X3D 16-Core Processor
  Uuid:                    CPU-XX                             
  Marketing Name:          AMD Ryzen 9 7950X3D 16-Core Processor
  Vendor Name:             CPU                                
  Feature:                 None specified                     
  Profile:                 FULL_PROFILE                       
  Float Round Mode:        NEAR                               
  Max Queue Number:        0(0x0)                             
  Queue Min Size:          0(0x0)                             
  Queue Max Size:          0(0x0)                             
  Queue Type:              MULTI                              
  Node:                    0                                  
  Device Type:             CPU                                
  Cache Info:              
    L1:                      32768(0x8000) KB                   
  Chip ID:                 0(0x0)                             
  ASIC Revision:           0(0x0)                             
  Cacheline Size:          64(0x40)                           
  Max Clock Freq. (MHz):   5763                               
  BDFID:                   0                                  
  Internal Node ID:        0                                  
  Compute Unit:            32                                 
  SIMDs per CU:            0                                  
  Shader Engines:          0                                  
  Shader Arrs. per Eng.:   0                                  
  WatchPts on Addr. Ranges:1                                  
  Memory Properties:       
  Features:                None
  Pool Info:               
    Pool 1                   
      Segment:                 GLOBAL; FLAGS: FINE GRAINED        
      Size:                    65427016(0x3e65648) KB             
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Recommended Granule:4KB                                
      Alloc Alignment:         4KB                                
      Accessible by all:       TRUE                               
    Pool 2                   
      Segment:                 GLOBAL; FLAGS: EXTENDED FINE GRAINED
      Size:                    65427016(0x3e65648) KB             
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Recommended Granule:4KB                                
      Alloc Alignment:         4KB                                
      Accessible by all:       TRUE                               
    Pool 3                   
      Segment:                 GLOBAL; FLAGS: KERNARG, FINE GRAINED
      Size:                    65427016(0x3e65648) KB             
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Recommended Granule:4KB                                
      Alloc Alignment:         4KB                                
      Accessible by all:       TRUE                               
    Pool 4                   
      Segment:                 GLOBAL; FLAGS: COARSE GRAINED      
      Size:                    65427016(0x3e65648) KB             
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Recommended Granule:4KB                                
      Alloc Alignment:         4KB                                
      Accessible by all:       TRUE                               
  ISA Info:                
*******                  
Agent 2                  
*******                  
  Name:                    gfx1100                            
  Uuid:                    GPU-fd9ca3bcfec72db2               
  Marketing Name:          Radeon RX 7900 GRE                 
  Vendor Name:             AMD                                
  Feature:                 KERNEL_DISPATCH                    
  Profile:                 BASE_PROFILE                       
  Float Round Mode:        NEAR                               
  Max Queue Number:        128(0x80)                          
  Queue Min Size:          64(0x40)                           
  Queue Max Size:          131072(0x20000)                    
  Queue Type:              MULTI                              
  Node:                    1                                  
  Device Type:             GPU                                
  Cache Info:              
    L1:                      32(0x20) KB                        
    L2:                      6144(0x1800) KB                    
    L3:                      65536(0x10000) KB                  
  Chip ID:                 29772(0x744c)                      
  ASIC Revision:           0(0x0)                             
  Cacheline Size:          128(0x80)                          
  Max Clock Freq. (MHz):   1927                               
  BDFID:                   768                                
  Internal Node ID:        1                                  
  Compute Unit:            80                                 
  SIMDs per CU:            2                                  
  Shader Engines:          6                                  
  Shader Arrs. per Eng.:   2                                  
  WatchPts on Addr. Ranges:4                                  
  Coherent Host Access:    FALSE                              
  Memory Properties:       
  Features:                KERNEL_DISPATCH 
  Fast F16 Operation:      TRUE                               
  Wavefront Size:          32(0x20)                           
  Workgroup Max Size:      1024(0x400)                        
  Workgroup Max Size per Dimension:
    x                        1024(0x400)                        
    y                        1024(0x400)                        
    z                        1024(0x400)                        
  Max Waves Per CU:        32(0x20)                           
  Max Work-item Per CU:    1024(0x400)                        
  Grid Max Size:           4294967295(0xffffffff)             
  Grid Max Size per Dimension:
    x                        4294967295(0xffffffff)             
    y                        4294967295(0xffffffff)             
    z                        4294967295(0xffffffff)             
  Max fbarriers/Workgrp:   32                                 
  Packet Processor uCode:: 542                                
  SDMA engine uCode::      24                                 
  IOMMU Support::          None                               
  Pool Info:               
    Pool 1                   
      Segment:                 GLOBAL; FLAGS: COARSE GRAINED      
      Size:                    16760832(0xffc000) KB              
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Recommended Granule:2048KB                             
      Alloc Alignment:         4KB                                
      Accessible by all:       FALSE                              
    Pool 2                   
      Segment:                 GLOBAL; FLAGS: EXTENDED FINE GRAINED
      Size:                    16760832(0xffc000) KB              
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Recommended Granule:2048KB                             
      Alloc Alignment:         4KB                                
      Accessible by all:       FALSE                              
    Pool 3                   
      Segment:                 GROUP                              
      Size:                    64(0x40) KB                        
      Allocatable:             FALSE                              
      Alloc Granule:           0KB                                
      Alloc Recommended Granule:0KB                                
      Alloc Alignment:         0KB                                
      Accessible by all:       FALSE                              
  ISA Info:                
    ISA 1                    
      Name:                    amdgcn-amd-amdhsa--gfx1100         
      Machine Models:          HSA_MACHINE_MODEL_LARGE            
      Profiles:                HSA_PROFILE_BASE                   
      Default Rounding Mode:   NEAR                               
      Default Rounding Mode:   NEAR                               
      Fast f16:                TRUE                               
      Workgroup Max Size:      1024(0x400)                        
      Workgroup Max Size per Dimension:
        x                        1024(0x400)                        
        y                        1024(0x400)                        
        z                        1024(0x400)                        
      Grid Max Size:           4294967295(0xffffffff)             
      Grid Max Size per Dimension:
        x                        4294967295(0xffffffff)             
        y                        4294967295(0xffffffff)             
        z                        4294967295(0xffffffff)             
      FBarrier Max Size:       32                                 
    ISA 2                    
      Name:                    amdgcn-amd-amdhsa--gfx11-generic   
      Machine Models:          HSA_MACHINE_MODEL_LARGE            
      Profiles:                HSA_PROFILE_BASE                   
      Default Rounding Mode:   NEAR                               
      Default Rounding Mode:   NEAR                               
      Fast f16:                TRUE                               
      Workgroup Max Size:      1024(0x400)                        
      Workgroup Max Size per Dimension:
        x                        1024(0x400)                        
        y                        1024(0x400)                        
        z                        1024(0x400)                        
      Grid Max Size:           4294967295(0xffffffff)             
      Grid Max Size per Dimension:
        x                        4294967295(0xffffffff)             
        y                        4294967295(0xffffffff)             
        z                        4294967295(0xffffffff)             
      FBarrier Max Size:       32                                 
*******                  
Agent 3                  
*******                  
  Name:                    gfx900                             
  Uuid:                    GPU-0215085621863084               
  Marketing Name:          Radeon RX Vega                     
  Vendor Name:             AMD                                
  Feature:                 KERNEL_DISPATCH                    
  Profile:                 BASE_PROFILE                       
  Float Round Mode:        NEAR                               
  Max Queue Number:        128(0x80)                          
  Queue Min Size:          64(0x40)                           
  Queue Max Size:          131072(0x20000)                    
  Queue Type:              MULTI                              
  Node:                    2                                  
  Device Type:             GPU                                
  Cache Info:              
    L1:                      16(0x10) KB                        
    L2:                      4096(0x1000) KB                    
  Chip ID:                 26751(0x687f)                      
  ASIC Revision:           1(0x1)                             
  Cacheline Size:          64(0x40)                           
  Max Clock Freq. (MHz):   1630                               
  BDFID:                   6656                               
  Internal Node ID:        2                                  
  Compute Unit:            64                                 
  SIMDs per CU:            4                                  
  Shader Engines:          4                                  
  Shader Arrs. per Eng.:   1                                  
  WatchPts on Addr. Ranges:4                                  
  Coherent Host Access:    FALSE                              
  Memory Properties:       
  Features:                KERNEL_DISPATCH 
  Fast F16 Operation:      TRUE                               
  Wavefront Size:          64(0x40)                           
  Workgroup Max Size:      1024(0x400)                        
  Workgroup Max Size per Dimension:
    x                        1024(0x400)                        
    y                        1024(0x400)                        
    z                        1024(0x400)                        
  Max Waves Per CU:        40(0x28)                           
  Max Work-item Per CU:    2560(0xa00)                        
  Grid Max Size:           4294967295(0xffffffff)             
  Grid Max Size per Dimension:
    x                        4294967295(0xffffffff)             
    y                        4294967295(0xffffffff)             
    z                        4294967295(0xffffffff)             
  Max fbarriers/Workgrp:   32                                 
  Packet Processor uCode:: 472                                
  SDMA engine uCode::      434                                
  IOMMU Support::          None                               
  Pool Info:               
    Pool 1                   
      Segment:                 GLOBAL; FLAGS: COARSE GRAINED      
      Size:                    8372224(0x7fc000) KB               
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Recommended Granule:2048KB                             
      Alloc Alignment:         4KB                                
      Accessible by all:       FALSE                              
    Pool 2                   
      Segment:                 GLOBAL; FLAGS: EXTENDED FINE GRAINED
      Size:                    8372224(0x7fc000) KB               
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Recommended Granule:2048KB                             
      Alloc Alignment:         4KB                                
      Accessible by all:       FALSE                              
    Pool 3                   
      Segment:                 GROUP                              
      Size:                    64(0x40) KB                        
      Allocatable:             FALSE                              
      Alloc Granule:           0KB                                
      Alloc Recommended Granule:0KB                                
      Alloc Alignment:         0KB                                
      Accessible by all:       FALSE                              
  ISA Info:                
    ISA 1                    
      Name:                    amdgcn-amd-amdhsa--gfx900:xnack-   
      Machine Models:          HSA_MACHINE_MODEL_LARGE            
      Profiles:                HSA_PROFILE_BASE                   
      Default Rounding Mode:   NEAR                               
      Default Rounding Mode:   NEAR                               
      Fast f16:                TRUE                               
      Workgroup Max Size:      1024(0x400)                        
      Workgroup Max Size per Dimension:
        x                        1024(0x400)                        
        y                        1024(0x400)                        
        z                        1024(0x400)                        
      Grid Max Size:           4294967295(0xffffffff)             
      Grid Max Size per Dimension:
        x                        4294967295(0xffffffff)             
        y                        4294967295(0xffffffff)             
        z                        4294967295(0xffffffff)             
      FBarrier Max Size:       32                                 
    ISA 2                    
      Name:                    amdgcn-amd-amdhsa--gfx9-generic:xnack-
      Machine Models:          HSA_MACHINE_MODEL_LARGE            
      Profiles:                HSA_PROFILE_BASE                   
      Default Rounding Mode:   NEAR                               
      Default Rounding Mode:   NEAR                               
      Fast f16:                TRUE                               
      Workgroup Max Size:      1024(0x400)                        
      Workgroup Max Size per Dimension:
        x                        1024(0x400)                        
        y                        1024(0x400)                        
        z                        1024(0x400)                        
      Grid Max Size:           4294967295(0xffffffff)             
      Grid Max Size per Dimension:
        x                        4294967295(0xffffffff)             
        y                        4294967295(0xffffffff)             
        z                        4294967295(0xffffffff)             
      FBarrier Max Size:       32                                 
*** Done ***
```e:                    16760832(0xffc000) KB              
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Recommended Granule:2048KB                             
      Alloc Alignment:         4KB                                
      Accessible by all:       FALSE                              
    Pool 2                   
      Segment:                 GLOBAL; FLAGS: EXTENDED FINE GRAINED
      Size:                    16760832(0xffc000) KB              
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Recommended Granule:2048KB                             
      Alloc Alignment:         4KB                                
      Accessible by all:       FALSE                              
    Pool 3                   
      Segment:                 GROUP                              
      Size:                    64(0x40) KB                        
      Allocatable:             FALSE                              
      Alloc Granule:           0KB                                
      Alloc Recommended Granule:0KB                                
      Alloc Alignment:         0KB                                
      Accessible by all:       FALSE                              
  ISA Info:                
    ISA 1                    
      Name:                    amdgcn-amd-amdhsa--gfx1100         
      Machine Models:          HSA_MACHINE_MODEL_LARGE            
      Profiles:                HSA_PROFILE_BASE                   
      Default Rounding Mode:   NEAR                               
      Default Rounding Mode:   NEAR                               
      Fast f16:                TRUE                               
      Workgroup Max Size:      1024(0x400)                        
      Workgroup Max Size per Dimension:
        x                        1024(0x400)                        
        y                        1024(0x400)                        
        z                        1024(0x400)                        
      Grid Max Size:           4294967295(0xffffffff)             
      Grid Max Size per Dimension:
        x                        4294967295(0xffffffff)             
        y                        4294967295(0xffffffff)             
        z                        4294967295(0xffffffff)             
      FBarrier Max Size:       32                                 
    ISA 2                    
      Name:                    amdgcn-amd-amdhsa--gfx11-generic   
      Machine Models:          HSA_MACHINE_MODEL_LARGE            
      Profiles:                HSA_PROFILE_BASE                   
      Default Rounding Mode:   NEAR                               
      Default Rounding Mode:   NEAR                               
      Fast f16:                TRUE                               
      Workgroup Max Size:      1024(0x400)                        
      Workgroup Max Size per Dimension:
        x                        1024(0x400)                        
        y                        1024(0x400)                        
        z                        1024(0x400)                        
      Grid Max Size:           4294967295(0xffffffff)             
      Grid Max Size per Dimension:
        x                        4294967295(0xffffffff)             
        y                        4294967295(0xffffffff)             
        z                        4294967295(0xffffffff)             
      FBarrier Max Size:       32                                 
*******                  
Agent 3                  
*******                  
  Name:                    gfx900                             
  Uuid:                    GPU-0215085621863084               
  Marketing Name:          Radeon RX Vega                     
  Vendor Name:             AMD                                
  Feature:                 KERNEL_DISPATCH                    
  Profile:                 BASE_PROFILE                       
  Float Round Mode:        NEAR                               
  Max Queue Number:        128(0x80)                          
  Queue Min Size:          64(0x40)                           
  Queue Max Size:          131072(0x20000)                    
  Queue Type:              MULTI                              
  Node:                    2                                  
  Device Type:             GPU                                
  Cache Info:              
    L1:                      16(0x10) KB                        
    L2:                      4096(0x1000) KB                    
  Chip ID:                 26751(0x687f)                      
  ASIC Revision:           1(0x1)                             
  Cacheline Size:          64(0x40)                           
  Max Clock Freq. (MHz):   1630                               
  BDFID:                   6656                               
  Internal Node ID:        2                                  
  Compute Unit:            64                                 
  SIMDs per CU:            4                                  
  Shader Engines:          4                                  
  Shader Arrs. per Eng.:   1                                  
  WatchPts on Addr. Ranges:4                                  
  Coherent Host Access:    FALSE                              
  Memory Properties:       
  Features:                KERNEL_DISPATCH 
  Fast F16 Operation:      TRUE                               
  Wavefront Size:          64(0x40)                           
  Workgroup Max Size:      1024(0x400)                        
  Workgroup Max Size per Dimension:
    x                        1024(0x400)                        
    y                        1024(0x400)                        
    z                        1024(0x400)                        
  Max Waves Per CU:        40(0x28)                           
  Max Work-item Per CU:    2560(0xa00)                        
  Grid Max Size:           4294967295(0xffffffff)             
  Grid Max Size per Dimension:
    x                        4294967295(0xffffffff)             
    y                        4294967295(0xffffffff)             
    z                        4294967295(0xffffffff)             
  Max fbarriers/Workgrp:   32                                 
  Packet Processor uCode:: 472                                
  SDMA engine uCode::      434                                
  IOMMU Support::          None                               
  Pool Info:               
    Pool 1                   
      Segment:                 GLOBAL; FLAGS: COARSE GRAINED      
      Size:                    8372224(0x7fc000) KB               
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Recommended Granule:2048KB                             
      Alloc Alignment:         4KB                                
      Accessible by all:       FALSE                              
    Pool 2                   
      Segment:                 GLOBAL; FLAGS: EXTENDED FINE GRAINED
      Size:                    8372224(0x7fc000) KB               
      Allocatable:             TRUE                               
      Alloc Granule:           4KB                                
      Alloc Recommended Granule:2048KB                             
      Alloc Alignment:         4KB                                
      Accessible by all:       FALSE                              
    Pool 3                   
      Segment:                 GROUP                              
      Size:                    64(0x40) KB                        
      Allocatable:             FALSE                              
      Alloc Granule:           0KB                                
      Alloc Recommended Granule:0KB                                
      Alloc Alignment:         0KB                                
      Accessible by all:       FALSE                              
  ISA Info:                
    ISA 1                    
      Name:                    amdgcn-amd-amdhsa--gfx900:xnack-   
      Machine Models:          HSA_MACHINE_MODEL_LARGE            
      Profiles:                HSA_PROFILE_BASE                   
      Default Rounding Mode:   NEAR                               
      Default Rounding Mode:   NEAR                               
      Fast f16:                TRUE                               
      Workgroup Max Size:      1024(0x400)                        
      Workgroup Max Size per Dimension:
        x                        1024(0x400)                        
        y                        1024(0x400)                        
        z                        1024(0x400)                        
      Grid Max Size:           4294967295(0xffffffff)             
      Grid Max Size per Dimension:
        x                        4294967295(0xffffffff)             
        y                        4294967295(0xffffffff)             
        z                        4294967295(0xffffffff)             
      FBarrier Max Size:       32                                 
    ISA 2                    
      Name:                    amdgcn-amd-amdhsa--gfx9-generic:xnack-
      Machine Models:          HSA_MACHINE_MODEL_LARGE            
      Profiles:                HSA_PROFILE_BASE                   
      Default Rounding Mode:   NEAR                               
      Default Rounding Mode:   NEAR                               
      Fast f16:                TRUE                               
      Workgroup Max Size:      1024(0x400)                        
      Workgroup Max Size per Dimension:
        x                        1024(0x400)                        
        y                        1024(0x400)                        
        z                        1024(0x400)                        
      Grid Max Size:           4294967295(0xffffffff)             
      Grid Max Size per Dimension:
        x                        4294967295(0xffffffff)             
        y                        4294967295(0xffffffff)             
        z                        4294967295(0xffffffff)             
      FBarrier Max Size:       32                                 
*** Done ***

[chowdri]

I think I'll try using vulkan instead of rocm to get somewhere with this.

[CsBigDataHub]

Also see detailed explanation here. containers/ramalama#1705 (comment)

I think I'll try using vulkan instead of rocm to get somewhere with this.

vulkan has not given me good results on AMD. Highly encourage you to try rocminfo and play with device id's.

[chowdri]

When using HIP_VISIBLE_DEVICES=0, the GPU is seen by llama-cli and llama-bench.

ggml_cuda_init: found 1 ROCm devices:
  Device 0: Radeon RX 7900 GRE, gfx1100 (0x1100), VMM: no, Wave Size: 32
build: 5898 (cbc68be5) with cc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0 for x86_64-linux-gnu
main: llama backend init
main: load the model and apply lora adapter, if any
llama_model_load_from_file_impl: using device ROCm0 (Radeon RX 7900 GRE) - 16312 MiB free

However, in llama-cli, none of the work is offloaded to GPU.

load_tensors: loading model tensors, this can take a while... (mmap = true)
load_tensors: offloading 0 repeating layers to GPU
load_tensors: offloaded 0/41 layers to GPU
load_tensors:   CPU_Mapped model buffer size = 14965.61 MiB

I've tried vulkan on lmstudio, and the performance in some cases is almost 2x of rocm. I don't know why but it is what is. Just need to check how vulkan works with llama.cpp

I opened this issue on rocm as well: ROCm/ROCm#4722 (comment)

Didnt get anywhere.

[CsBigDataHub]

Thanks for the info, good luck.