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:
- 788c9622ad2694bfecc3d495364e87ac33c54d968069b00a2361f87d5f9afaf5
- Size of remote file:
- 110 MB
- SHA256:
- e7c49e143e2805a4f08b26f730a31be311c6a44374fc3e11ddebd6dd4cfa3c3a
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