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DeepLearner101
/
ImageNetSelectedSubsetBasedModel-Trained

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

Instructions to use DeepLearner101/ImageNetSelectedSubsetBasedModel-Trained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use DeepLearner101/ImageNetSelectedSubsetBasedModel-Trained with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="DeepLearner101/ImageNetSelectedSubsetBasedModel-Trained")
    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("DeepLearner101/ImageNetSelectedSubsetBasedModel-Trained")
    model = AutoModelForImageClassification.from_pretrained("DeepLearner101/ImageNetSelectedSubsetBasedModel-Trained")
  • Notebooks
  • Google Colab
  • Kaggle
ImageNetSelectedSubsetBasedModel-Trained
283 MB
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  • 1 contributor
History: 8 commits
DeepLearner101's picture
DeepLearner101
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  • .gitattributes
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  • best_hyperparameters.json
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  • config.json
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  • hyperparameters_tuning_results.csv
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  • pytorch_model_0010.pth
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  • pytorch_model_0030.pth
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  • pytorch_model_0048.pth
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  • training_metrics_0010.json
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  • training_metrics_0030.json
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  • training_metrics_0048.json
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