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
Download cla.PNG from ErnestBeckham/ViT-Lungs: direct link, hf CLI and curl.
- Browser
- Download file 7.41 kB
-
https://huggingface.co/ErnestBeckham/ViT-Lungs/resolve/main/cla.PNG
- Command line
-
hf download hf://ErnestBeckham/ViT-Lungs/cla.PNG
-
curl -L -o cla.PNG https://huggingface.co/ErnestBeckham/ViT-Lungs/resolve/main/cla.PNG
7.41 kB