Instructions to use dedgington/vit-small-ds with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use dedgington/vit-small-ds with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://dedgington/vit-small-ds") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 713feb019273a841767b6039f945089a7139cc110d55bbb148b977fc20f349af
- Size of remote file:
- 2.08 MB
- SHA256:
- 55de94fea6d8bfc491b9c72fe37c56a673108b61fcf3f202f45d25408b846cbc
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