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sidushdid
/
ViT-base-patch16-BUSI-Mendeley-AdamW

Image Classification
Transformers
Safetensors
vit
medical
biology
ultrasound
breast cancer
Model card Files Files and versions
xet
Community

Instructions to use sidushdid/ViT-base-patch16-BUSI-Mendeley-AdamW with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use sidushdid/ViT-base-patch16-BUSI-Mendeley-AdamW with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="sidushdid/ViT-base-patch16-BUSI-Mendeley-AdamW")
    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("sidushdid/ViT-base-patch16-BUSI-Mendeley-AdamW")
    model = AutoModelForImageClassification.from_pretrained("sidushdid/ViT-base-patch16-BUSI-Mendeley-AdamW", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
ViT-base-patch16-BUSI-Mendeley-AdamW
343 MB
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  • 1 contributor
History: 3 commits
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sidushdid
Update README.md
e15fc9f verified over 2 years ago
  • .gitattributes
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  • README.md
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  • all_results.json
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  • config.json
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  • eval_results.json
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  • model.safetensors
    343 MB
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  • pred_results.json
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  • preprocessor_config.json
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  • train_results.json
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  • trainer_state.json
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  • training_args.bin
    4.66 kB
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