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gilgmesh
/
gil-clip

Zero-Shot Image Classification
Transformers
Safetensors
gil_clip
feature-extraction
clip
fashion-clip
vision
multimodal
fashion
custom_code
Model card Files Files and versions
xet
Community

Instructions to use gilgmesh/gil-clip with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use gilgmesh/gil-clip with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("zero-shot-image-classification", model="gilgmesh/gil-clip", trust_remote_code=True)
    pipe(
        "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png",
        candidate_labels=["animals", "humans", "landscape"],
    )
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("gilgmesh/gil-clip", trust_remote_code=True, dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
gil-clip
613 MB
Ctrl+K
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  • 1 contributor
History: 6 commits
gilgmesh's picture
gilgmesh
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  • README.md
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  • config.json
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  • configuration_gil_clip.py
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  • example_full.png
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  • example_top.png
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  • merges.txt
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  • model.safetensors
    607 MB
    xet
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  • modeling_gil_clip.py
    4.68 kB
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  • preprocessor_config.json
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  • special_tokens_map.json
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  • tokenizer.json
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  • tokenizer_config.json
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  • vocab.json
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