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sgugger
/
custom-resnet

Image Classification
Transformers
PyTorch
resnet
custom_code
Model card Files Files and versions
xet
Community
1

Instructions to use sgugger/custom-resnet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use sgugger/custom-resnet with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="sgugger/custom-resnet", trust_remote_code=True)
    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("sgugger/custom-resnet", trust_remote_code=True)
    model = AutoModelForImageClassification.from_pretrained("sgugger/custom-resnet", trust_remote_code=True)
  • Notebooks
  • Google Colab
  • Kaggle
custom-resnet
103 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
sgugger's picture
sgugger
commit files to HF hub
2350837 about 4 years ago
  • .gitattributes
    1.18 kB
    initial commit about 4 years ago
  • config.json
    556 Bytes
    commit files to HF hub about 4 years ago
  • configuration_resnet.py
    1.14 kB
    commit files to HF hub about 4 years ago
  • modeling_resnet.py
    1.56 kB
    commit files to HF hub about 4 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    103 MB
    xet
    commit files to HF hub about 4 years ago