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pytholic
/
vit_classification_huggingface

Image Classification
Transformers
PyTorch
TensorBoard
vit
huggingpics
Eval Results (legacy)
Model card Files Files and versions
xet
Metrics Training metrics Community
1

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

  • Libraries
  • Transformers

    How to use pytholic/vit_classification_huggingface with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="pytholic/vit_classification_huggingface")
    pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")
    # Load model directly
    from transformers import AutoImageProcessor, AutoModelForImageClassification
    
    processor = AutoImageProcessor.from_pretrained("pytholic/vit_classification_huggingface")
    model = AutoModelForImageClassification.from_pretrained("pytholic/vit_classification_huggingface")
  • Notebooks
  • Google Colab
  • Kaggle
vit_classification_huggingface
344 MB
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  • 1 contributor
History: 8 commits
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pytholic
commit files to HF hub
ee1aa63 over 3 years ago
  • data
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  • images
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  • runs
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  • .gitattributes
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  • README.md
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  • config.json
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  • preprocessor_config.json
    325 Bytes
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  • pytorch_model.bin

    Detected Pickle imports (3)

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

    What is a pickle import?

    343 MB
    xet
    commit files to HF hub over 3 years ago