Daniel Bevenius 4a46d2b792
llava : remove prog parameter from ArgumentParser (#5457)
* llava: remove prog parameter from ArgumentParser

This commit removes the `prog` parameter from `ArgumentParser`
so that it uses the default value which is the name of the script.

The motivation for this change is that currently the usage output looks
like this:
```console
$ python examples/llava/convert-image-encoder-to-gguf.py --help
usage: convert_hf_to_gguf.py [-h] ...
```
And with this change it will look like this:
```console
$ python examples/llava/convert-image-encoder-to-gguf.py --help
usage: convert-image-encoder-to-gguf.py [-h] ...
```

Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>

* ci: add W503 to flake8 ignore list

This commit adds W503 to the ignore list for flake8. This is done to
avoid the following error:
W503 line break before binary operator

Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>

---------

Signed-off-by: Daniel Bevenius <daniel.bevenius@gmail.com>
2024-02-12 10:38:44 +02:00
..
2024-01-22 15:09:35 +02:00
2024-02-12 09:16:06 +02:00
2023-12-30 23:24:42 +02:00
2023-12-30 23:24:42 +02:00

LLaVA

Currently this implementation supports llava-v1.5 variants.

The pre-converted 7b and 13b models are available.

After API is confirmed, more models will be supported / uploaded.

Usage

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

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

./llava-cli -m ../llava-v1.5-7b/ggml-model-f16.gguf --mmproj ../llava-v1.5-7b/mmproj-model-f16.gguf --image path/to/an/image.jpg

note: A lower temperature like 0.1 is recommended for better quality. add --temp 0.1 to the command to do so.

Model conversion

  • Clone llava-v15-7b and clip-vit-large-patch14-336 locally:
git clone https://huggingface.co/liuhaotian/llava-v1.5-7b

git clone https://huggingface.co/openai/clip-vit-large-patch14-336
  1. Install the required Python packages:
pip install -r examples/llava/requirements.txt
  1. Use llava-surgery.py to split the LLaVA model to LLaMA and multimodel projector constituents:
python ./examples/llava/llava-surgery.py -m ../llava-v1.5-7b
  1. Use convert-image-encoder-to-gguf.py to convert the LLaVA image encoder to GGUF:
python ./examples/llava/convert-image-encoder-to-gguf.py -m ../clip-vit-large-patch14-336 --llava-projector ../llava-v1.5-7b/llava.projector --output-dir ../llava-v1.5-7b
  1. Use convert.py to convert the LLaMA part of LLaVA to GGUF:
python ./convert.py ../llava-v1.5-7b

Now both the LLaMA part and the image encoder is in the llava-v1.5-7b directory.

TODO

  • Support non-CPU backend for the image encoding part.
  • Support different sampling methods.
  • Support more model variants.