Xuan-Son Nguyen edb18b6e8f clip : fix pixtral on some GPU backends (#13097) 8 месяцев назад
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android 243453533e llava : update documentations (#13055) 9 месяцев назад
CMakeLists.txt 84a9bf2fc2 mtmd : merge llava, gemma3 and minicpmv CLI into single `llama-mtmd-cli` (#13012) 9 месяцев назад
README-quantize.md 1ec208083c llava: add quantization for the visual projector LLAVA, Qwen2VL (#11644) 11 месяцев назад
README.md ecda2ec4b3 mtmd : Support Pixtral 12B (#13065) 8 месяцев назад
clip-impl.h 13be08daf9 clip : remove boi/eoi embeddings for GLM-edge model (#13081) 8 месяцев назад
clip-quantize-cli.cpp 1ec208083c llava: add quantization for the visual projector LLAVA, Qwen2VL (#11644) 11 месяцев назад
clip.cpp edb18b6e8f clip : fix pixtral on some GPU backends (#13097) 8 месяцев назад
clip.h 6602304814 llava: fix errors in clip.h on certain compilers (#13030) 9 месяцев назад
convert_image_encoder_to_gguf.py e9b2f84f14 llava: add big-endian conversion for image encoder (#12218) 10 месяцев назад
deprecation-warning.cpp 84a9bf2fc2 mtmd : merge llava, gemma3 and minicpmv CLI into single `llama-mtmd-cli` (#13012) 9 месяцев назад
glmedge-convert-image-encoder-to-gguf.py 0cec062a63 llama : add support for GLM-Edge and GLM-Edge-V series models (#10573) 11 месяцев назад
glmedge-surgery.py 0cec062a63 llama : add support for GLM-Edge and GLM-Edge-V series models (#10573) 11 месяцев назад
llava.cpp 0c50923944 clip : use smart pointer (⚠️ breaking change) (#12869) 9 месяцев назад
llava.h 3071c0a5f2 llava : support MiniCPM-V-2.5 (#7599) 1 год назад
llava_surgery.py e235b267a2 py : switch to snake_case (#8305) 1 год назад
llava_surgery_v2.py 7a2c913e66 llava : Add Granite Vision Support (#11794) 10 месяцев назад
minicpmv-convert-image-encoder-to-gguf.py 8352cdc87b llava : fix bug in minicpm-v code (#11513) 10 месяцев назад
minicpmv-surgery.py 3e3357fd77 llava : support Minicpm-omni (#11289) 1 год назад
mtmd-cli.cpp 7c727fbe39 arg : add --no-mmproj-offload (#13093) 8 месяцев назад
mtmd.cpp 13be08daf9 clip : remove boi/eoi embeddings for GLM-edge model (#13081) 8 месяцев назад
mtmd.h b9154ecff9 mtmd : add methods to access `mtmd_image_tokens` (#12906) 9 месяцев назад
qwen2_vl_surgery.py 4ddd199f6f llava : Allow locally downloaded models for QwenVL (#10833) 1 год назад
qwen2vl-cli.cpp 0364178ca2 clip : refactor clip_init, add tests (#12757) 9 месяцев назад
requirements.txt d3ae0ee8d7 py : fix requirements check '==' -> '~=' (#8982) 1 год назад
test-1.jpeg 0364178ca2 clip : refactor clip_init, add tests (#12757) 9 месяцев назад
tests.sh ecda2ec4b3 mtmd : Support Pixtral 12B (#13065) 8 месяцев назад

README-quantize.md

Quantizing CLIP Visual Projector

This is the tool for quantizing the CLIP visual projector model. Quantization reduces the precision of the model's weights, which can significantly decrease the model size and improve inference speed, often with minimal impact on performance.

Usage

To quantize a CLIP visual projector model, use the following command:

./bin/llama-llava-clip-quantize-cli /path/to/ggml-model-f32.gguf /path/to/ggml-model-quantized.gguf <type>

After the quantization, the visual projector can be used freely with the existing LLAVA cli (LLAVA, Qwen2VL, etc).

Arguments

  • /path/to/ggml-model-f32.gguf: The path to the input model file in FP32 or FP16 format.
  • /path/to/ggml-model-quantized.gguf: The path where the quantized model will be saved.
  • <type>: The quantization type to apply. This should be an integer corresponding to one of the quantization types defined in the enum ggml_type.

Quantization Types

The following quantization types are supported, based on the enum ggml_type definition:

  • 2 - q4_0: 4-bit quantization with a single scale value.
  • 3 - q4_1: 4-bit quantization with a separate scale value for each block.
  • 6 - q5_0: 5-bit quantization with a single scale value.
  • 7 - q5_1: 5-bit quantization with a separate scale value for each block.
  • 8 - q8_0: 8-bit quantization with a single scale value.

Example

To quantize a model using the q4_0 quantization type, you would run:

./bin/llama-llava-clip-quantize-cli /path/to/ggml-model-f32.gguf /path/to/ggml-model-quantized.gguf 2

This command will generate a quantized model at /path/to/ggml-model-quantized.gguf using the q4_0 quantization method.

Notes

  • Quantization can lead to a loss in model accuracy, depending on the chosen quantization type. It is recommended to evaluate the quantized model's performance on your specific task to ensure it meets your requirements.
  • The quantized model will typically be smaller in size and faster to run, making it more suitable for deployment in resource-constrained environments.