Instructions to use wangrice/icd_embedding_models with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use wangrice/icd_embedding_models with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://wangrice/icd_embedding_models") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6900c501bebd611d2ae6d6dd0d2b01f1fde7b2c5f36febdfb3409bbd8b216c2d
- Size of remote file:
- 1.52 MB
- SHA256:
- 98062e3dcc722cb18f0afa3e58ad28f6b1c14ff546b756a427198f6291169a87
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