llama : add support for EmbeddingGemma 300m #15798
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This commit add support for the EmbeddingGemma 300m. This model supports sliding window attention (SWA) and a new swq_type is introduced to support symmetric SWA masking. This commit also extracts the code from the function llama_is_masked_swa in llama-impl.h, so that the logic can be shared by both llm_graph_input_attn_no_cache::set_input and llama_kv_cache::set_input_kq_mask. With this commit the EmbeddingGemma 300m model can be converted to to GGUF and used with llama.cpp. Once the model has been uploaded to HuggingFace it can be used like this: ```console ./build/bin/llama-cli -hf ggml-org/embeddinggemma-300m-GGUF:Q8_0 ```
ggerganov
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Sep 4, 2025
gabe-l-hart
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Sep 5, 2025
…g-model-disabled-agent-prefill * origin/master: (84 commits) CUDA: fastdiv, launch bounds for mmvq + q8_1 quant (ggml-org#15802) tests : add --list-ops and --show-coverage options (ggml-org#15745) gguf: gguf_writer refactor (ggml-org#15691) kv-cache : fix SWA checks + disable cacheless iSWA (ggml-org#15811) model-conversion : add --embeddings flag to modelcard.template [no ci] (ggml-org#15801) chat : fixed crash when Hermes 2 <tool_call> had a newline before it (ggml-org#15639) chat : nemotron thinking & toolcalling support (ggml-org#15676) scripts : add Jinja tester PySide6 simple app (ggml-org#15756) llama : add support for EmbeddingGemma 300m (ggml-org#15798) metal : Add template specialization for mul_mm_id w/ ne20 == 10 (ggml-org#15799) llama : set n_outputs to 1 to avoid 0 outputs mean-pooling (ggml-org#15791) CANN: Refactor ND to NZ workspace to be per-device (ggml-org#15763) server: add exceed_context_size_error type (ggml-org#15780) Document the new max GPU layers default in help (ggml-org#15771) ggml: add ops for WAN video model (cuda && cpu) (ggml-org#15669) CANN: Fix precision issue on 310I DUO multi-devices (ggml-org#15784) opencl: add hs=40 to FA (ggml-org#15758) CANN: fix acl_rstd allocation size in ggml_cann_rms_norm (ggml-org#15760) vulkan: fix mmv subgroup16 selection (ggml-org#15775) vulkan: don't use std::string in load_shaders, to improve compile time (ggml-org#15724) ...
gabe-l-hart
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…upport * origin/master: Thinking model disabled assistant prefill (ggml-org#15404) Implement --log-colors with always/never/auto (ggml-org#15792) CUDA: fastdiv, launch bounds for mmvq + q8_1 quant (ggml-org#15802) tests : add --list-ops and --show-coverage options (ggml-org#15745) gguf: gguf_writer refactor (ggml-org#15691) kv-cache : fix SWA checks + disable cacheless iSWA (ggml-org#15811) model-conversion : add --embeddings flag to modelcard.template [no ci] (ggml-org#15801) chat : fixed crash when Hermes 2 <tool_call> had a newline before it (ggml-org#15639) chat : nemotron thinking & toolcalling support (ggml-org#15676) scripts : add Jinja tester PySide6 simple app (ggml-org#15756) llama : add support for EmbeddingGemma 300m (ggml-org#15798)
danbev
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Sep 6, 2025
This commit updates the requirements to support converting Embedding Gemma 300m models. The motivation for this change is that during development I had a local copy of the transformers package which is what I used for converting the models. This was a mistake on my part and I should have also updated my transformers version to the official release. I had checked the requirements/requirements-convert_legacy_llama.txt file and noted that the version was >=4.45.1,<5.0.0 and came to the conculusion that no updated would be needed, this assumed that Embedding Gemma would be in a transformers release at the time Commit fb15d64 ("llama : add support for EmbeddingGemma 300m (ggml-org#15798)) was merged. So anyone wanting to convert themselves would be able to do so. However, Embedding Gemma is a preview release and this commit updates the requirements to use this preview release.
walidbr
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Sep 7, 2025
This commit add support for the EmbeddingGemma 300m. This model supports sliding window attention (SWA) and a new swq_type is introduced to support symmetric SWA masking. This commit also extracts the code from the function llama_is_masked_swa in llama-impl.h, so that the logic can be shared by both llm_graph_input_attn_no_cache::set_input and llama_kv_cache::set_input_kq_mask. With this commit the EmbeddingGemma 300m model can be converted to to GGUF and used with llama.cpp. Once the model has been uploaded to HuggingFace it can be used like this: ```console ./build/bin/llama-cli -hf ggml-org/embeddinggemma-300m-GGUF:Q8_0 ```
danbev
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Sep 9, 2025
* requirements : update transformers/torch for Embedding Gemma This commit updates the requirements to support converting Embedding Gemma 300m models. The motivation for this change is that during development I had a local copy of the transformers package which is what I used for converting the models. This was a mistake on my part and I should have also updated my transformers version to the official release. I had checked the requirements/requirements-convert_legacy_llama.txt file and noted that the version was >=4.45.1,<5.0.0 and came to the conculusion that no updated would be needed, this assumed that Embedding Gemma would be in a transformers release at the time Commit fb15d64 ("llama : add support for EmbeddingGemma 300m (#15798)) was merged. So anyone wanting to convert themselves would be able to do so. However, Embedding Gemma is a preview release and this commit updates the requirements to use this preview release. * resolve additional python dependencies * fix pyright errors in tokenizer test and remove unused import
njsyw1997
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Sep 10, 2025
…g#15828) * requirements : update transformers/torch for Embedding Gemma This commit updates the requirements to support converting Embedding Gemma 300m models. The motivation for this change is that during development I had a local copy of the transformers package which is what I used for converting the models. This was a mistake on my part and I should have also updated my transformers version to the official release. I had checked the requirements/requirements-convert_legacy_llama.txt file and noted that the version was >=4.45.1,<5.0.0 and came to the conculusion that no updated would be needed, this assumed that Embedding Gemma would be in a transformers release at the time Commit fb15d64 ("llama : add support for EmbeddingGemma 300m (ggml-org#15798)) was merged. So anyone wanting to convert themselves would be able to do so. However, Embedding Gemma is a preview release and this commit updates the requirements to use this preview release. * resolve additional python dependencies * fix pyright errors in tokenizer test and remove unused import
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This commit add support for the EmbeddingGemma 300m. This model supports sliding window attention (SWA) and a new swq_type is introduced to support symmetric SWA masking.
This commit also extracts the code from the function llama_is_masked_swa in llama-impl.h, so that the logic can be shared by both llm_graph_input_attn_no_cache::set_input and llama_kv_cache::set_input_kq_mask.
With this commit the EmbeddingGemma 300m model can be converted to to GGUF and used with llama.cpp.
Once the model has been uploaded to HuggingFace it can be used like this:
llama-embedding -hf ggml-org/embeddinggemma-300m-GGUF:Q8_0