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daking
/
custom-resnet50d

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

Instructions to use daking/custom-resnet50d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use daking/custom-resnet50d with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="daking/custom-resnet50d", 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("daking/custom-resnet50d", trust_remote_code=True)
    model = AutoModelForImageClassification.from_pretrained("daking/custom-resnet50d", trust_remote_code=True)
  • Notebooks
  • Google Colab
  • Kaggle
custom-resnet50d
103 MB
Ctrl+K
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  • 2 contributors
History: 2 commits
daking's picture
daking
Upload model
3096448 about 3 years ago
  • .gitattributes
    1.48 kB
    initial commit about 3 years ago
  • config.json
    551 Bytes
    Upload model about 3 years ago
  • configuration_resnet.py
    1.15 kB
    Upload model about 3 years ago
  • modeling_resnet.py
    1.74 kB
    Upload model about 3 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    103 MB
    xet
    Upload model about 3 years ago