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bswift
/
RETfound_eyepacs_DR

Image Classification
Transformers
PyTorch
vit
VitMAE
Model card Files Files and versions
xet
Community
1

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

  • Libraries
  • Transformers

    How to use bswift/RETfound_eyepacs_DR with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="bswift/RETfound_eyepacs_DR")
    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("bswift/RETfound_eyepacs_DR")
    model = AutoModelForImageClassification.from_pretrained("bswift/RETfound_eyepacs_DR", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
RETfound_eyepacs_DR
6.07 GB
Ctrl+K
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  • 1 contributor
History: 12 commits
SFconvertbot's picture
SFconvertbot
Adding `safetensors` variant of this model
d5a8cd8 verified over 1 year ago
  • predictions
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  • README.md
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  • _metrics_test.csv
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  • checkpoint-best.pth
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  • config.json
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  • dataset_info.json
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  • model.safetensors
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  • model_card.json
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  • preprocessor_config.json
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  • requirements.txt
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  • training_config.json
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