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flaviagiammarino
/
pubmed-clip-vit-base-patch32

Zero-Shot Image Classification
Transformers
PyTorch
google-tensorflow TensorFlow
JAX
English
clip
medical
vision
Model card Files Files and versions
xet
Community
3

Instructions to use flaviagiammarino/pubmed-clip-vit-base-patch32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use flaviagiammarino/pubmed-clip-vit-base-patch32 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("zero-shot-image-classification", model="flaviagiammarino/pubmed-clip-vit-base-patch32")
    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("flaviagiammarino/pubmed-clip-vit-base-patch32")
    model = AutoModelForZeroShotImageClassification.from_pretrained("flaviagiammarino/pubmed-clip-vit-base-patch32")
  • Notebooks
  • Google Colab
  • Kaggle
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Easy evaluation of the zero-shot capabilities of pubmedclip

#3 opened about 2 years ago by
fhvilshoj

Adding `safetensors` variant of this model

#2 opened about 2 years ago by
SFconvertbot

Adding `safetensors` variant of this model

#1 opened over 2 years ago by
SFconvertbot
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