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:
- c1e49f53c760e207c138f6a468481cdfe242c6593a6ae9fd6241e6b263927081
- Size of remote file:
- 110 MB
- SHA256:
- ce4faee77c968db305fd2db6c2000379ea3a6d5fe4d4ee8f8e3b5973b9c50c65
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