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Warning

THIS PROJECT IS ARCHIVED
Intel will not provide or guarantee development of or support for this project, including but not limited to, maintenance, bug fixes, new releases or updates.

Patches to this project are no longer accepted by Intel.

LVLM-Interpret: An Interpretability Tool for Large Vision-Language Models

[Project Page] [Paper]

Setup

  • Update submodules

    git submodule update --init --recursive

  • Install dependencies

    pip install -r requirements.txt

Usage

Start the Gradio server:

python app.py --model_name_or_path Intel/llava-gemma-2b --load_8bit 

or

python app.py --model_name_or_path llava-hf/llava-1.5-7b-hf --load_8bit

Options:

usage: app.py [-h] [--model_name_or_path MODEL_NAME_OR_PATH] [--host HOST] [--port PORT] [--share] [--embed] [--load_4bit] [--load_8bit]

options:
  -h, --help            show this help message and exit
  --model_name_or_path MODEL_NAME_OR_PATH
                        Model name or path to load the model from
  --host HOST           Host to run the server on
  --port PORT           Port to run the server on
  --share               Whether to share the server on Gradio's public server
  --embed               Whether to run the server in an iframe
  --load_4bit           Whether to load the model in 4bit
  --load_8bit           Whether to load the model in 8bit

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