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webnn
/
efficientnet-lite4

Image Classification
Transformers
ONNX
resnet
Model card Files Files and versions
xet
Community

Instructions to use webnn/efficientnet-lite4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use webnn/efficientnet-lite4 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="webnn/efficientnet-lite4")
    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("webnn/efficientnet-lite4")
    model = AutoModelForImageClassification.from_pretrained("webnn/efficientnet-lite4")
  • Notebooks
  • Google Colab
  • Kaggle
efficientnet-lite4 / onnx
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  • 1 contributor
History: 18 commits
captainspock's picture
captainspock
Upload model_fp16.onnx
0f01093 verified about 2 years ago
  • model_fp16.onnx
    26 MB
    xet
    Upload model_fp16.onnx about 2 years ago
  • model_fp16_original.onnx
    26 MB
    xet
    Rename onnx/model_fp16.onnx to onnx/model_fp16_original.onnx about 2 years ago
  • model_with_softmax_fp16.onnx
    26 MB
    xet
    Rename onnx/model_fp16.onnx to onnx/model_with_softmax_fp16.onnx about 2 years ago