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Sovego
/
clip_vit_base_32_make_model

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

Instructions to use Sovego/clip_vit_base_32_make_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Sovego/clip_vit_base_32_make_model with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("zero-shot-image-classification", model="Sovego/clip_vit_base_32_make_model")
    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("Sovego/clip_vit_base_32_make_model")
    model = AutoModelForZeroShotImageClassification.from_pretrained("Sovego/clip_vit_base_32_make_model")
  • Notebooks
  • Google Colab
  • Kaggle
clip_vit_base_32_make_model
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  • 1 contributor
History: 9 commits
Sovego's picture
Sovego
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  • .gitattributes
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  • README.md
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  • config.json
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  • merges.txt
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  • model.safetensors
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  • pytorch_model.bin

    Detected Pickle imports (4)

    • "collections.OrderedDict",
    • "torch.FloatStorage",
    • "torch._utils._rebuild_tensor_v2",
    • "torch.LongStorage"

    What is a pickle import?

    605 MB
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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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