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:
- c259b40b2c7c44e5e3ea9f64ce82065d76f549bc8e6793ef8ea058b56004f8a7
- Size of remote file:
- 262 MB
- SHA256:
- 2e90faa4df15bd6538caa5a24e826a6c513598cab8e87fcb2a1ed34fdc6e763c
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