Instructions to use mlx-community/idefics2-8b-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/idefics2-8b-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-8bit") config = load_config("mlx-community/idefics2-8b-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) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Typo of `mlx-vlm`
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# mlx-community/idefics2-8b-8bit
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This model was converted to MLX format from [`HuggingFaceM4/idefics2-8b`]() using mlx-
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Refer to the [original model card](https://huggingface.co/HuggingFaceM4/idefics2-8b) for more details on the model.
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## Use with mlx
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# mlx-community/idefics2-8b-8bit
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This model was converted to MLX format from [`HuggingFaceM4/idefics2-8b`]() using mlx-vlm version **0.0.4**.
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Refer to the [original model card](https://huggingface.co/HuggingFaceM4/idefics2-8b) for more details on the model.
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## Use with mlx
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