Instructions to use probing-vits/vit_b16_patch16_224_i1k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use probing-vits/vit_b16_patch16_224_i1k with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://probing-vits/vit_b16_patch16_224_i1k") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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## References
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[1] An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale: https://arxiv.org/abs/2010.11929
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[2] How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers: https://arxiv.org/abs/2106.10270
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## References
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[1] An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale: https://arxiv.org/abs/2010.11929
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[2] How to train your ViT? Data, Augmentation, and Regularization in Vision Transformers: https://arxiv.org/abs/2106.10270
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