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llm-jp
/
waon-siglip2-base-patch16-256

Zero-Shot Image Classification
Transformers
Safetensors
siglip
vision
Model card Files Files and versions
xet
Community

Instructions to use llm-jp/waon-siglip2-base-patch16-256 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use llm-jp/waon-siglip2-base-patch16-256 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("zero-shot-image-classification", model="llm-jp/waon-siglip2-base-patch16-256")
    pipe(
        "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png",
        candidate_labels=["animals", "humans", "landscape"],
    )
    # Load model directly
    from transformers import AutoProcessor, AutoModelForZeroShotImageClassification
    
    processor = AutoProcessor.from_pretrained("llm-jp/waon-siglip2-base-patch16-256")
    model = AutoModelForZeroShotImageClassification.from_pretrained("llm-jp/waon-siglip2-base-patch16-256")
  • Notebooks
  • Google Colab
  • Kaggle
waon-siglip2-base-patch16-256
1.54 GB
Ctrl+K
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  • 1 contributor
History: 7 commits
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  • model.safetensors
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  • preprocessor_config.json
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  • tokenizer.json
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  • tokenizer.model
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