Instructions to use nico9ga/fruits-Classification-Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use nico9ga/fruits-Classification-Model with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://nico9ga/fruits-Classification-Model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ab418da6f346bfc14c5a91777ebfe4609585f33e13c6fc092d36fa9c30b653de
- Size of remote file:
- 57 Bytes
- SHA256:
- bd7b391c8f1c8c0de4e468ba81ce8b76d0608a766cb5799d22cfac6b8fd6751d
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