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llama.cpp/examples/llava/README-glmedge.md
piDack 0cec062a63
llama : add support for GLM-Edge and GLM-Edge-V series models (#10573) 
* add glm edge chat model

* use config partial_rotary_factor as rope ratio

* support for glm edge model

* vision model support

* remove debug info

* fix format

* llava.cpp trailing whitespace

* remove unused AutoTokenizer

* Update src/llama.cpp for not contain <|end|> or </s>

Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>

* add edge template

* fix chat template

* fix confict

* fix confict

* fix ci err

* fix format err

* fix template err

* 9b hf chat support

* format

* format clip.cpp

* fix format

* Apply suggestions from code review

* Apply suggestions from code review

* Update examples/llava/clip.cpp

* fix format

* minor : style

---------

Co-authored-by: liyuhang <yuhang.li@zhipuai.cn>
Co-authored-by: piDack <pcdack@hotmail.co>
Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
Co-authored-by: liyuhang <yuhang.li@aminer.cn>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2025-02-02 09:48:46 +02:00

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GLMV-EDGE

Currently this implementation supports glm-edge-v-2b and glm-edge-v-5b.

Usage

Build with cmake or run make llama-llava-cli to build it.

After building, run: ./llama-llava-cli to see the usage. For example:

./llama-llava-cli -m model_path/ggml-model-f16.gguf --mmproj model_path/mmproj-model-f16.gguf --image img_path/image.jpg -p "<|system|>\n system prompt <image><|user|>\n prompt <|assistant|>\n"

note: A lower temperature like 0.1 is recommended for better quality. add --temp 0.1 to the command to do so. note: For GPU offloading ensure to use the -ngl flag just like usual

GGUF conversion

  1. Clone a GLMV-EDGE model (2B or 5B). For example:
git clone https://huggingface.co/THUDM/glm-edge-v-5b or https://huggingface.co/THUDM/glm-edge-v-2b
  1. Use glmedge-surgery.py to split the GLMV-EDGE model to LLM and multimodel projector constituents:
python ./examples/llava/glmedge-surgery.py -m ../model_path
  1. Use glmedge-convert-image-encoder-to-gguf.py to convert the GLMV-EDGE image encoder to GGUF:
python ./examples/llava/glmedge-convert-image-encoder-to-gguf.py -m ../model_path --llava-projector ../model_path/glm.projector --output-dir ../model_path
  1. Use examples/convert_hf_to_gguf.py to convert the LLM part of GLMV-EDGE to GGUF:
python convert_hf_to_gguf.py ../model_path

Now both the LLM part and the image encoder are in the model_path directory.