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joaodaniel
/
rs-clip-cap4

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

Instructions to use joaodaniel/rs-clip-cap4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use joaodaniel/rs-clip-cap4 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("zero-shot-image-classification", model="joaodaniel/rs-clip-cap4")
    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("joaodaniel/rs-clip-cap4")
    model = AutoModelForZeroShotImageClassification.from_pretrained("joaodaniel/rs-clip-cap4")
  • Notebooks
  • Google Colab
  • Kaggle
rs-clip-cap4
1.72 GB
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  • 1 contributor
History: 5 commits
joaodaniel's picture
joaodaniel
Update README.md
c91ad34 verified about 1 year ago
  • .gitattributes
    1.52 kB
    initial commit about 1 year ago
  • README.md
    2.25 kB
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  • config.json
    717 Bytes
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  • 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
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