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EZCon
/
SmolVLM2-2.2B-Instruct-mlx

Image-Text-to-Text
MLX
Safetensors
English
smolvlm
video-text-to-text
conversational
Model card Files Files and versions
xet
Community

Instructions to use EZCon/SmolVLM2-2.2B-Instruct-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • MLX

    How to use EZCon/SmolVLM2-2.2B-Instruct-mlx 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("EZCon/SmolVLM2-2.2B-Instruct-mlx")
    config = load_config("EZCon/SmolVLM2-2.2B-Instruct-mlx")
    
    # 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
SmolVLM2-2.2B-Instruct-mlx
4.5 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
hermeschen-ezcon's picture
hermeschen-ezcon
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f6cd5ac verified about 1 month ago
  • .gitattributes
    1.52 kB
    initial commit about 1 month ago
  • README.md
    1.08 kB
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  • added_tokens.json
    4.74 kB
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  • chat_template.jinja
    403 Bytes
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  • chat_template.json
    430 Bytes
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  • config.json
    4.38 kB
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  • generation_config.json
    136 Bytes
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  • model.safetensors
    4.49 GB
    xet
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  • model.safetensors.index.json
    53.6 kB
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  • preprocessor_config.json
    599 Bytes
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  • processor_config.json
    713 Bytes
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  • special_tokens_map.json
    868 Bytes
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  • tokenizer.json
    3.55 MB
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  • tokenizer_config.json
    848 Bytes
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  • vocab.json
    801 kB
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