Instructions to use ErnestBeckham/MulticancerViT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use ErnestBeckham/MulticancerViT with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://ErnestBeckham/MulticancerViT") - Notebooks
- Google Colab
- Kaggle
Download saved_model.pb from ErnestBeckham/MulticancerViT: direct link, hf CLI and curl.
- Browser
- Download file 3.39 MB
-
https://huggingface.co/ErnestBeckham/MulticancerViT/resolve/main/saved_model.pb
- Command line
-
hf download hf://ErnestBeckham/MulticancerViT/saved_model.pb
-
curl -L -o saved_model.pb https://huggingface.co/ErnestBeckham/MulticancerViT/resolve/main/saved_model.pb
3.39 MB
- Xet hash:
- 04e2d9fdbd6b9941109c252509cb206e62b212a2a4c335ac9dd71d50ec4c48c0
- Size of remote file:
- 3.39 MB
- SHA256:
- db08a0bf20604746bd6995f60f6354e852e0b473d22d6d45676748a7c08f91a9
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