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PumpkinCat
/
CLIP-ViT-L14-ScoreRS30

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

Instructions to use PumpkinCat/CLIP-ViT-L14-ScoreRS30 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use PumpkinCat/CLIP-ViT-L14-ScoreRS30 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("zero-shot-image-classification", model="PumpkinCat/CLIP-ViT-L14-ScoreRS30")
    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("PumpkinCat/CLIP-ViT-L14-ScoreRS30")
    model = AutoModelForZeroShotImageClassification.from_pretrained("PumpkinCat/CLIP-ViT-L14-ScoreRS30")
  • Notebooks
  • Google Colab
  • Kaggle
CLIP-ViT-L14-ScoreRS30
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  • 1 contributor
History: 4 commits
PumpkinCat's picture
PumpkinCat
Update config.json
bab78fc verified about 1 year ago
  • .gitattributes
    1.52 kB
    initial commit about 1 year ago
  • README.md
    5.17 kB
    Upload model about 1 year ago
  • config.json
    781 Bytes
    Update config.json about 1 year ago
  • merges.txt
    525 kB
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  • model.safetensors
    1.71 GB
    xet
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  • preprocessor_config.json
    504 Bytes
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  • special_tokens_map.json
    588 Bytes
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  • tokenizer.json
    3.64 MB
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  • tokenizer_config.json
    774 Bytes
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  • vocab.json
    862 kB
    Upload processor about 1 year ago