Instructions to use Rathious/NutritionalModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use Rathious/NutritionalModel with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://Rathious/NutritionalModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2e3d0897290af8d1affeaa674e72ea684aa7b10e44b9399902efe9a944f81ffd
- Size of remote file:
- 262 MB
- SHA256:
- 6dd2a6b8667692db2bd29979bfcf0750996936a81243e4b8f791d256aff76080
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