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facebook
/
metaclip-2-worldwide-l14

Zero-Shot Image Classification
Transformers
Safetensors
metaclip_2
clip
multilingual
Model card Files Files and versions
xet
Community

Instructions to use facebook/metaclip-2-worldwide-l14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use facebook/metaclip-2-worldwide-l14 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("zero-shot-image-classification", model="facebook/metaclip-2-worldwide-l14")
    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("facebook/metaclip-2-worldwide-l14")
    model = AutoModelForZeroShotImageClassification.from_pretrained("facebook/metaclip-2-worldwide-l14")
  • Notebooks
  • Google Colab
  • Kaggle
metaclip-2-worldwide-l14
4.41 GB
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  • 2 contributors
History: 2 commits
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voidism
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  • .gitattributes
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  • README.md
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  • config.json
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  • model.safetensors
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  • preprocessor_config.json
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  • sentencepiece.bpe.model
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  • special_tokens_map.json
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  • tokenizer.json
    61.3 MB
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  • tokenizer_config.json
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