Some models like gemma-3n crashes - rocBLAS error: Cannot read /opt/rocm-6.4.1/lib/llvm/bin/../../../lib/rocblas/library/TensileLibrary.dat: No such file or directory for GPU arch : gfx1036 #14421
Description
Some models works, some models crashes
llama-cli -m /models/gemma-3n-E4B-it-Q4_K_M.gguf --jinja --single-turn -sys "You are a helpful assistant" -p "Hello"
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: 1 (f667f1e) 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 (AMD Radeon Graphics) - 23642 MiB free
llama_model_loader: loaded meta data with 41 key-value pairs and 847 tensors from /models/gemma-3n-E4B-it-Q4_K_M.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 = gemma3n
llama_model_loader: - kv 1: general.type str = model
llama_model_loader: - kv 2: general.name str = Gemma-3N-E4B-It
llama_model_loader: - kv 3: general.finetune str = 3n-E4B-it
llama_model_loader: - kv 4: general.basename str = Gemma-3N-E4B-It
llama_model_loader: - kv 5: general.quantized_by str = Unsloth
llama_model_loader: - kv 6: general.size_label str = 6.9B
llama_model_loader: - kv 7: general.repo_url str = https://huggingface.co/unsloth
llama_model_loader: - kv 8: gemma3n.context_length u32 = 32768
llama_model_loader: - kv 9: gemma3n.embedding_length u32 = 2048
llama_model_loader: - kv 10: gemma3n.block_count u32 = 35
llama_model_loader: - kv 11: gemma3n.feed_forward_length u32 = 16384
llama_model_loader: - kv 12: gemma3n.attention.head_count u32 = 8
llama_model_loader: - kv 13: gemma3n.attention.layer_norm_rms_epsilon f32 = 0.000001
llama_model_loader: - kv 14: gemma3n.attention.key_length u32 = 256
llama_model_loader: - kv 15: gemma3n.attention.value_length u32 = 256
llama_model_loader: - kv 16: gemma3n.rope.freq_base f32 = 1000000.000000
llama_model_loader: - kv 17: gemma3n.attention.sliding_window u32 = 512
llama_model_loader: - kv 18: gemma3n.attention.head_count_kv u32 = 2
llama_model_loader: - kv 19: gemma3n.altup.active_idx u32 = 0
llama_model_loader: - kv 20: gemma3n.altup.num_inputs u32 = 4
llama_model_loader: - kv 21: gemma3n.embedding_length_per_layer_input u32 = 256
llama_model_loader: - kv 22: gemma3n.attention.shared_kv_layers f32 = 15.000000
llama_model_loader: - kv 23: gemma3n.activation_sparsity_scale arr[f32,35] = [1.644854, 1.644854, 1.644854, 1.6448...
llama_model_loader: - kv 24: gemma3n.attention.sliding_window_pattern arr[bool,35] = [true, true, true, true, false, true,...
llama_model_loader: - kv 25: tokenizer.chat_template str = {{ bos_token }}\n{%- if messages[0]['r...
llama_model_loader: - kv 26: tokenizer.ggml.model str = llama
llama_model_loader: - kv 27: tokenizer.ggml.pre str = default
llama_model_loader: - kv 28: tokenizer.ggml.tokens arr[str,262144] = ["<pad>", "<eos>", "<bos>", "<unk>", ...
llama_model_loader: - kv 29: tokenizer.ggml.scores arr[f32,262144] = [-1000.000000, -1000.000000, -1000.00...
llama_model_loader: - kv 30: tokenizer.ggml.token_type arr[i32,262144] = [3, 3, 3, 3, 3, 4, 3, 3, 3, 3, 3, 3, ...
llama_model_loader: - kv 31: tokenizer.ggml.bos_token_id u32 = 2
llama_model_loader: - kv 32: tokenizer.ggml.eos_token_id u32 = 106
llama_model_loader: - kv 33: tokenizer.ggml.unknown_token_id u32 = 3
llama_model_loader: - kv 34: tokenizer.ggml.padding_token_id u32 = 0
llama_model_loader: - kv 35: tokenizer.ggml.add_bos_token bool = true
llama_model_loader: - kv 36: tokenizer.ggml.add_sep_token bool = false
llama_model_loader: - kv 37: tokenizer.ggml.add_eos_token bool = false
llama_model_loader: - kv 38: tokenizer.ggml.add_space_prefix bool = false
llama_model_loader: - kv 39: general.quantization_version u32 = 2
llama_model_loader: - kv 40: general.file_type u32 = 15
llama_model_loader: - type f32: 422 tensors
llama_model_loader: - type q4_K: 282 tensors
llama_model_loader: - type q6_K: 35 tensors
llama_model_loader: - type bf16: 108 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type = Q4_K - Medium
print_info: file size = 3.94 GiB (4.93 BPW)
load: special tokens cache size = 6414
load: token to piece cache size = 1.9446 MB
print_info: arch = gemma3n
print_info: vocab_only = 0
print_info: n_ctx_train = 32768
print_info: n_embd = 2048
print_info: n_layer = 35
print_info: n_head = 8
print_info: n_head_kv = 2
print_info: n_rot = 256
print_info: n_swa = 512
print_info: is_swa_any = 1
print_info: n_embd_head_k = 256
print_info: n_embd_head_v = 256
print_info: n_gqa = 4
print_info: n_embd_k_gqa = 512
print_info: n_embd_v_gqa = 512
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 = 1.0e+00
print_info: n_ff = 16384
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: 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 = E4B
print_info: model params = 6.87 B
print_info: general.name = Gemma-3N-E4B-It
print_info: vocab type = SPM
print_info: n_vocab = 262144
print_info: n_merges = 0
print_info: BOS token = 2 '<bos>'
print_info: EOS token = 106 '<end_of_turn>'
print_info: EOT token = 106 '<end_of_turn>'
print_info: UNK token = 3 '<unk>'
print_info: PAD token = 0 '<pad>'
print_info: LF token = 248 '<0x0A>'
print_info: EOG token = 106 '<end_of_turn>'
print_info: max token length = 48
load_tensors: loading model tensors, this can take a while... (mmap = true)
load_tensors: offloading 0 repeating layers to GPU
load_tensors: offloaded 0/36 layers to GPU
load_tensors: CPU_Mapped model buffer size = 4034.52 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 = 1.00 MiB
llama_kv_cache_unified_iswa: creating non-SWA KV cache, size = 4096 cells
llama_kv_cache_unified: CPU KV buffer size = 32.00 MiB
llama_kv_cache_unified: size = 32.00 MiB ( 4096 cells, 4 layers, 1 seqs), K (f16): 16.00 MiB, V (f16): 16.00 MiB
llama_kv_cache_unified_iswa: creating SWA KV cache, size = 1024 cells
llama_kv_cache_unified: CPU KV buffer size = 32.00 MiB
llama_kv_cache_unified: size = 32.00 MiB ( 1024 cells, 16 layers, 1 seqs), K (f16): 16.00 MiB, V (f16): 16.00 MiB
llama_context: ROCm0 compute buffer size = 940.00 MiB
llama_context: ROCm_Host compute buffer size = 31.51 MiB
llama_context: graph nodes = 3266
llama_context: graph splits = 843 (with bs=512), 6 (with bs=1)
common_init_from_params: KV cache shifting is not supported for this context, disabling KV cache shifting
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 = 8
main: chat template is available, enabling conversation mode (disable it with -no-cnv)
main: chat template example:
<start_of_turn>user
You are a helpful assistant
Hello<end_of_turn>
<start_of_turn>model
Hi there<end_of_turn>
<start_of_turn>user
How are you?<end_of_turn>
<start_of_turn>model
system_info: n_threads = 8 (n_threads_batch = 8) / 16 | 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 |
sampler seed: 3368873966
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
user
You are a helpful assistant
Hello
model
rocBLAS error: Cannot read /opt/rocm-6.4.1/lib/llvm/bin/../../../lib/rocblas/library/TensileLibrary.dat: No such file or directory for GPU arch : gfx1036
List of available TensileLibrary Files :
"/opt/rocm-6.4.1/lib/llvm/bin/../../../lib/rocblas/library/TensileLibrary_lazy_gfx1201.dat"
"/opt/rocm-6.4.1/lib/llvm/bin/../../../lib/rocblas/library/TensileLibrary_lazy_gfx942.dat"
"/opt/rocm-6.4.1/lib/llvm/bin/../../../lib/rocblas/library/TensileLibrary_lazy_gfx908.dat"
"/opt/rocm-6.4.1/lib/llvm/bin/../../../lib/rocblas/library/TensileLibrary_lazy_gfx1030.dat"
"/opt/rocm-6.4.1/lib/llvm/bin/../../../lib/rocblas/library/TensileLibrary_lazy_gfx90a.dat"
"/opt/rocm-6.4.1/lib/llvm/bin/../../../lib/rocblas/library/TensileLibrary_lazy_gfx1200.dat"
"/opt/rocm-6.4.1/lib/llvm/bin/../../../lib/rocblas/library/TensileLibrary_lazy_gfx1100.dat"
"/opt/rocm-6.4.1/lib/llvm/bin/../../../lib/rocblas/library/TensileLibrary_lazy_gfx1101.dat"
"/opt/rocm-6.4.1/lib/llvm/bin/../../../lib/rocblas/library/TensileLibrary_lazy_gfx1102.dat"
Aborted (core dumped)
This works
llama-cli -m /models/gemma-3-12b-it-Q4_K_M.gguf --jinja --single-turn -sys "You are a helpful assistant" -p "Hello"
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: 1 (f667f1e) with cc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0 for x86_64-linux-gnu
main: llama backend init
...
system_info: n_threads = 8 (n_threads_batch = 8) / 16 | 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 |
sampler seed: 115469656
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
user
You are a helpful assistant
Hello
model
Hello! It's nice to hear from you. 😊
How can I help you today? Let me know what you need! [end of text]
llama_perf_sampler_print: sampling time = 3.45 ms / 45 runs ( 0.08 ms per token, 13039.70 tokens per second)
llama_perf_context_print: load time = 1087.73 ms
llama_perf_context_print: prompt eval time = 582.84 ms / 16 tokens ( 36.43 ms per token, 27.45 tokens per second)
llama_perf_context_print: eval time = 5768.43 ms / 28 runs ( 206.02 ms per token, 4.85 tokens per second)
llama_perf_context_print: total time = 6369.64 ms / 44 tokens
llama-cli --list-devices
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
Available devices:
ROCm0: AMD Radeon Graphics (23675 MiB, 23642 MiB free)
llama-cli --version
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
version: 1 (f667f1e)
built with cc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0 for x86_64-linux-gnu