HuggingFaceM4/the_cauldron
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How to use mlx-community/idefics2-8b-chatty-8bit with MLX:
# Make sure mlx-vlm is installed
# pip install --upgrade mlx-vlm
from mlx_vlm import load, generate
from mlx_vlm.prompt_utils import apply_chat_template
from mlx_vlm.utils import load_config
# Load the model
model, processor = load("mlx-community/idefics2-8b-chatty-8bit")
config = load_config("mlx-community/idefics2-8b-chatty-8bit")
# Prepare input
image = ["http://images.cocodataset.org/val2017/000000039769.jpg"]
prompt = "Describe this image."
# Apply chat template
formatted_prompt = apply_chat_template(
processor, config, prompt, num_images=1
)
# Generate output
output = generate(model, processor, formatted_prompt, image)
print(output)This model was converted to MLX format from HuggingFaceM4/idefics2-8b-chatty using mlx-vlm version 0.1.0.
Refer to the original model card for more details on the model.
pip install -U mlx-vlm
python -m mlx_vlm.generate --model mlx-community/idefics2-8b-chatty-8bit --max-tokens 100 --temp 0.0
Quantized
# Make sure mlx-vlm is installed # pip install --upgrade mlx-vlm from mlx_vlm import load, generate from mlx_vlm.prompt_utils import apply_chat_template from mlx_vlm.utils import load_config # Load the model model, processor = load("mlx-community/idefics2-8b-chatty-8bit") config = load_config("mlx-community/idefics2-8b-chatty-8bit") # Prepare input image = ["http://images.cocodataset.org/val2017/000000039769.jpg"] prompt = "Describe this image." # Apply chat template formatted_prompt = apply_chat_template( processor, config, prompt, num_images=1 ) # Generate output output = generate(model, processor, formatted_prompt, image) print(output)