Instructions to use ErnestBeckham/ViT-Lungs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use ErnestBeckham/ViT-Lungs with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://ErnestBeckham/ViT-Lungs") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 35de028b25d54bbf112ec615e6665f468d1ce3bb98c001f797540473f82e3cbe
- Size of remote file:
- 4.75 MB
- SHA256:
- 01ab46ae4248bc1834c8febeddf865f172f1e46372fd8177d11f54d68aa9c62b
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