From 15a333260ab637a040ed0864c206a2ceaf806bb8 Mon Sep 17 00:00:00 2001 From: Jian Liao Date: Thu, 14 Mar 2024 04:18:23 -0700 Subject: [PATCH] readme : improve readme for Llava-1.6 example (#6044) Co-authored-by: Jian Liao --- examples/llava/README.md | 18 +++++++++++++----- 1 file changed, 13 insertions(+), 5 deletions(-) diff --git a/examples/llava/README.md b/examples/llava/README.md index 35e6d9e5d..67cb0f22b 100644 --- a/examples/llava/README.md +++ b/examples/llava/README.md @@ -63,12 +63,20 @@ Now both the LLaMA part and the image encoder is in the `llava-v1.5-7b` director ```console git clone https://huggingface.co/liuhaotian/llava-v1.6-vicuna-7b ``` -2) Use `llava-surgery-v2.py` which also supports llava-1.5 variants pytorch as well as safetensor models: + +2) Install the required Python packages: + +```sh +pip install -r examples/llava/requirements.txt +``` + +3) Use `llava-surgery-v2.py` which also supports llava-1.5 variants pytorch as well as safetensor models: ```console python examples/llava/llava-surgery-v2.py -C -m ../llava-v1.6-vicuna-7b/ ``` - you will find a llava.projector and a llava.clip file in your model directory -3) Copy the llava.clip file into a subdirectory (like vit), rename it to pytorch_model.bin and add a fitting vit configuration to the directory: + +4) Copy the llava.clip file into a subdirectory (like vit), rename it to pytorch_model.bin and add a fitting vit configuration to the directory: ```console mkdir vit cp ../llava-v1.6-vicuna-7b/llava.clip vit/pytorch_model.bin @@ -76,18 +84,18 @@ cp ../llava-v1.6-vicuna-7b/llava.projector vit/ curl -s -q https://huggingface.co/cmp-nct/llava-1.6-gguf/raw/main/config_vit.json -o vit/config.json ``` -4) Create the visual gguf model: +5) Create the visual gguf model: ```console python ./examples/llava/convert-image-encoder-to-gguf.py -m vit --llava-projector vit/llava.projector --output-dir vit --clip-model-is-vision ``` - This is similar to llava-1.5, the difference is that we tell the encoder that we are working with the pure vision model part of CLIP -5) Then convert the model to gguf format: +6) Then convert the model to gguf format: ```console python ./convert.py ../llava-v1.6-vicuna-7b/ --skip-unknown ``` -6) And finally we can run the llava-cli using the 1.6 model version: +7) And finally we can run the llava-cli using the 1.6 model version: ```console ./llava-cli -m ../llava-v1.6-vicuna-7b/ggml-model-f16.gguf --mmproj vit/mmproj-model-f16.gguf --image some-image.jpg -c 4096 ```