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BabyChou
/
vit-base-patch16-imagenette

Image Classification
Transformers
JAX
vit
Model card Files Files and versions
xet
Community

Instructions to use BabyChou/vit-base-patch16-imagenette with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use BabyChou/vit-base-patch16-imagenette with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("image-classification", model="BabyChou/vit-base-patch16-imagenette")
    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("BabyChou/vit-base-patch16-imagenette")
    model = AutoModelForImageClassification.from_pretrained("BabyChou/vit-base-patch16-imagenette")
  • Notebooks
  • Google Colab
  • Kaggle
vit-base-patch16-imagenette
343 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
BabyChou's picture
BabyChou
Saving weights and logs of epoch 0
7a2ad7f over 3 years ago
  • .gitattributes
    1.34 kB
    initial commit over 3 years ago
  • config.json
    958 Bytes
    Saving weights and logs of epoch 0 over 3 years ago
  • flax_model.msgpack
    343 MB
    xet
    Saving weights and logs of epoch 0 over 3 years ago