Instructions to use AiresPucrs/Cifar-CNN with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use AiresPucrs/Cifar-CNN with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://AiresPucrs/Cifar-CNN") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5d0363c96909328d3d50861cf31c62238120bd8f9f312637f4ef8e7397726d15
- Size of remote file:
- 58 Bytes
- SHA256:
- 4b5131f0ddb8da8388ce58c87ca1ad0e811182941fff33deb523c3e012973bae
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