Instructions to use ml-debi/EfficientNetB0-Food101 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use ml-debi/EfficientNetB0-Food101 with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://ml-debi/EfficientNetB0-Food101") - Notebooks
- Google Colab
- Kaggle
Upload 3 files
Browse files- fingerprint.pb +3 -0
- keras_metadata.pb +3 -0
- saved_model.pb +3 -0
fingerprint.pb
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keras_metadata.pb
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saved_model.pb
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oid sha256:bff39e1de7e904149ce580258c57cb665781024df0efac96663cf43e590b3548
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size 5203606
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