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Zannatul
/
microsoft_swinv2-tiny-patch4-window8-256-batch_16_epoch_4_classes_24_final_withAug

Image Classification
Transformers
TensorBoard
Safetensors
swinv2
Generated from Trainer
Eval Results (legacy)
Model card Files Files and versions
xet
Metrics Training metrics Community

Instructions to use Zannatul/microsoft_swinv2-tiny-patch4-window8-256-batch_16_epoch_4_classes_24_final_withAug with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use Zannatul/microsoft_swinv2-tiny-patch4-window8-256-batch_16_epoch_4_classes_24_final_withAug with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="Zannatul/microsoft_swinv2-tiny-patch4-window8-256-batch_16_epoch_4_classes_24_final_withAug")
    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("Zannatul/microsoft_swinv2-tiny-patch4-window8-256-batch_16_epoch_4_classes_24_final_withAug")
    model = AutoModelForImageClassification.from_pretrained("Zannatul/microsoft_swinv2-tiny-patch4-window8-256-batch_16_epoch_4_classes_24_final_withAug")
  • Notebooks
  • Google Colab
  • Kaggle
microsoft_swinv2-tiny-patch4-window8-256-batch_16_epoch_4_classes_24_final_withAug / runs
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  • 1 contributor
History: 2 commits
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Zannatul
๐Ÿป cheers
ec6c855 verified about 2 years ago
  • May09_14-30-54_ed3f40b4fac8
    ๐Ÿป cheers about 2 years ago