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oohtmeel
/
swin-tiny-patch4-finetuned-lung-cancer-ct-scans

Image Classification
Transformers
Safetensors
swin
medical
biology
Scans
CT
Model card Files Files and versions
xet
Community

Instructions to use oohtmeel/swin-tiny-patch4-finetuned-lung-cancer-ct-scans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use oohtmeel/swin-tiny-patch4-finetuned-lung-cancer-ct-scans with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="oohtmeel/swin-tiny-patch4-finetuned-lung-cancer-ct-scans")
    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("oohtmeel/swin-tiny-patch4-finetuned-lung-cancer-ct-scans")
    model = AutoModelForImageClassification.from_pretrained("oohtmeel/swin-tiny-patch4-finetuned-lung-cancer-ct-scans", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
swin-tiny-patch4-finetuned-lung-cancer-ct-scans
111 MB
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  • 1 contributor
History: 30 commits
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oohtmeel
Update README.md
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    initial commit about 2 years ago
  • README.md
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  • config.json
    1.13 kB
    Training in progress, epoch 0 about 2 years ago
  • model.safetensors
    110 MB
    xet
    Training in progress, epoch 6 about 2 years ago
  • preprocessor_config.json
    626 Bytes
    Training in progress, epoch 0 about 2 years ago
  • training_args.bin
    5.18 kB
    xet
    Training in progress, epoch 0 about 2 years ago