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ENOT-AutoDL
/
imagenet-benchmark

Image Classification
Transformers
ONNX
ENOT-AutoDL
Model card Files Files and versions
xet
Community

Instructions to use ENOT-AutoDL/imagenet-benchmark with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use ENOT-AutoDL/imagenet-benchmark with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="ENOT-AutoDL/imagenet-benchmark")
    pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("ENOT-AutoDL/imagenet-benchmark", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
imagenet-benchmark / ResNet-50
236 MB
Ctrl+K
Ctrl+K
  • 3 contributors
History: 1 commit
andreysher's picture
andreysher
imagenet-benchmark
4d679c2 about 3 years ago
  • ResNet50-ENOT-x2.onnx
    50.7 MB
    xet
    imagenet-benchmark about 3 years ago
  • ResNet50-ENOT-x2.pth
    102 MB
    xet
    imagenet-benchmark about 3 years ago
  • ResNet50-ENOT-x4.onnx
    20.9 MB
    xet
    imagenet-benchmark about 3 years ago
  • ResNet50-ENOT-x4.pth
    62.2 MB
    xet
    imagenet-benchmark about 3 years ago