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rbanfield
/
clip-vit-large-patch14

Zero-Shot Image Classification
Transformers
PyTorch
google-tensorflow TensorFlow
JAX
Safetensors
clip
vision
Model card Files Files and versions
xet
Community
1

Instructions to use rbanfield/clip-vit-large-patch14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use rbanfield/clip-vit-large-patch14 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("zero-shot-image-classification", model="rbanfield/clip-vit-large-patch14")
    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("rbanfield/clip-vit-large-patch14")
    model = AutoModelForZeroShotImageClassification.from_pretrained("rbanfield/clip-vit-large-patch14")
  • Notebooks
  • Google Colab
  • Kaggle
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Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Added binary file handing to inference endpoint and made return value a dictionary

#1 opened over 2 years ago by
nicklorch
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