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:
- 32d81d859ae1c3e5bf298ecdb49551f8c59fe4fcb55e1b8d01eee7db13c9b9ec
- Size of remote file:
- 95.4 MB
- SHA256:
- 281a958793cf09b8c000ebb90e4fce386c997d2d7db8dbbd647be59aaaa7988d
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