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DunnBC22
/
efficientnet-b5-Brain_Tumors_Image_Classification

Image Classification
Transformers
PyTorch
TensorBoard
efficientnet
Generated from Trainer
Eval Results (legacy)
Model card Files Files and versions
xet
Metrics Training metrics Community
1

Instructions to use DunnBC22/efficientnet-b5-Brain_Tumors_Image_Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use DunnBC22/efficientnet-b5-Brain_Tumors_Image_Classification with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="DunnBC22/efficientnet-b5-Brain_Tumors_Image_Classification")
    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("DunnBC22/efficientnet-b5-Brain_Tumors_Image_Classification")
    model = AutoModelForImageClassification.from_pretrained("DunnBC22/efficientnet-b5-Brain_Tumors_Image_Classification")
  • Notebooks
  • Google Colab
  • Kaggle
efficientnet-b5-Brain_Tumors_Image_Classification / runs
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  • 1 contributor
History: 4 commits
DunnBC22's picture
DunnBC22
Model save
9300356 almost 3 years ago
  • Jun10_13-40-33_Brians-Mac-mini.local
    Model save almost 3 years ago