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sr29
/
Mage-VL-mlx-4bit

Image-Text-to-Text
MLX
Safetensors
mage_vl
apple-silicon
vision-language
video
streaming
conversational
custom_code
4-bit precision
Model card Files Files and versions
xet
Community

Instructions to use sr29/Mage-VL-mlx-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • MLX

    How to use sr29/Mage-VL-mlx-4bit 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("sr29/Mage-VL-mlx-4bit")
    config = load_config("sr29/Mage-VL-mlx-4bit")
    
    # 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
Mage-VL-mlx-4bit
3.16 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
sr29's picture
sr29
Update README.md
c39d802 verified 13 days ago
  • .gitattributes
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  • README.md
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  • added_tokens.json
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  • chat_template.jinja
    1.02 kB
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  • config.json
    3.37 kB
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  • generation_config.json
    121 Bytes
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  • merges.txt
    1.67 MB
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  • model.safetensors
    3.14 GB
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  • model.safetensors.index.json
    99 kB
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  • preprocessor_config.json
    1.81 kB
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  • special_tokens_map.json
    613 Bytes
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  • tokenizer.json
    11.4 MB
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  • tokenizer_config.json
    4.75 kB
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  • video_preprocessor_config.json
    465 Bytes
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  • vocab.json
    2.78 MB
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