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SpotLab
/
MobileNetClassification

Image Classification
Transformers
PyTorch
google-tensorflow TensorFlow
LiteRT
mobilenet_v2
vision
Model card Files Files and versions
xet
Community
1

Instructions to use SpotLab/MobileNetClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use SpotLab/MobileNetClassification with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="SpotLab/MobileNetClassification")
    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("SpotLab/MobileNetClassification")
    model = AutoModelForImageClassification.from_pretrained("SpotLab/MobileNetClassification")
  • Notebooks
  • Google Colab
  • Kaggle
MobileNetClassification
35.4 MB
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  • 2 contributors
History: 11 commits
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jaimegarcia
Update README.md
19223c1 over 2 years ago
  • .gitattributes
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    initial commit over 2 years ago
  • README.md
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  • config.json
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  • preprocessor_config.json
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  • pytorch_model.bin

    Detected Pickle imports (4)

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

    What is a pickle import?

    14.3 MB
    xet
    Upload pytorch_model.bin over 2 years ago
  • tf_model.h5
    10.9 MB
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  • tflite_model.tflite
    10.2 MB
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