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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")
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("ENOT-AutoDL/imagenet-benchmark", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
imagenet-benchmark
426 MB
Ctrl+K
Ctrl+K
  • 3 contributors
History: 9 commits
andreysher's picture
andreysher
Create config.json
85257cc verified over 2 years ago
  • MobileNetV2
    Update checkpoints over 2 years ago
  • ResNet-50
    imagenet-benchmark over 2 years ago
  • ViT-B-32
    add ViT x4.8 ONNX, small fixes in test.py, and allow measuring macs on ONNX over 2 years ago
  • .gitattributes
    1.52 kB
    initial commit over 2 years ago
  • README.md
    2.06 kB
    Update checkpoints over 2 years ago
  • config.json
    24 Bytes
    Create config.json over 2 years ago
  • measure_mac.py
    1.33 kB
    add ViT x4.8 ONNX, small fixes in test.py, and allow measuring macs on ONNX over 2 years ago
  • requirements.txt
    115 Bytes
    add ViT x4.8 ONNX, small fixes in test.py, and allow measuring macs on ONNX over 2 years ago
  • test.py
    5.27 kB
    add ViT x4.8 ONNX, small fixes in test.py, and allow measuring macs on ONNX over 2 years ago
  • utils.py
    6.28 kB
    imagenet-benchmark over 2 years ago