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
Upload 2 files
Browse files- final_nutrition_model.h5 +3 -0
- label_mean_std.json +1 -0
final_nutrition_model.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:6dd2a6b8667692db2bd29979bfcf0750996936a81243e4b8f791d256aff76080
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size 261725880
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label_mean_std.json
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{"mean": [252.92308044433594, 12.18520736694336, 22.860946655273438, 13.142603874206543], "std": [170.64926147460938, 10.814655303955078, 19.008207321166992, 14.321125030517578]}
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