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* add: llava mlx first draft * add: weights comparision * add forward pass skeleton * update: now imports weights correctly * delete base * latest * adding config * fix: use config * add mlx config * feat: add image processor for llava processor * wip * feat: llava working example * chore: refactor generate script * chore: clean up * add: warning to user if no <image> token despite using one * add: __call__ to LlavaModel * add: call to LlavaModel * update fp * clean up var names * update: native GeLU * Cleanup * update generate and readme * remove todo comment * rearrange tests * fix example code * nits in README * update readme * nit in readme * nits in README * chore(llava): refactor image embedding merging logic * min mlx version * nits in readmes * fix cli prompt, some nits * updates, slight simplify --------- Co-authored-by: anchen <li.anchen.au@gmail.com> Co-authored-by: Awni Hannun <awni@apple.com>
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1.3 KiB
LLaVA
An example of LLaVA: Large Language and Vision Assistant in MLX.1 LLlava is a multimodal model that can generate text given combined image and text inputs.
Setup
Install the dependencies:
pip install -r requirements.txt
Run
You can use LLaVA to ask questions about images.
For example, using the command line:
python generate.py \
--model llava-hf/llava-1.5-7b-hf \
--image "http://images.cocodataset.org/val2017/000000039769.jpg" \
--prompt "USER: <image>\nWhat are these?\nASSISTANT:" \
--max-tokens 128 \
--temp 0
This uses the following image:
And generates the output:
These are two cats lying on a pink couch.
You can also use LLaVA in Python:
from generate import load_model, prepare_inputs, generate_text
processor, model = load_model("llava-hf/llava-1.5-7b-hf")
max_tokens, temperature = 128, 0.0
prompt = "USER: <image>\nWhat are these?\nASSISTANT:"
image = "http://images.cocodataset.org/val2017/000000039769.jpg"
input_ids, pixel_values = prepare_inputs(processor, image, prompt)
reply = generate_text(
input_ids, pixel_values, model, processor, max_tokens, temperature
)
print(reply)
-
Refer to LLaVA project webpage for more information. ↩︎