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:
- adef0543fa995b7346ec4eeccca92ca256e2e0e6927bec05cfe6c8ff458ef811
- Size of remote file:
- 48.4 kB
- SHA256:
- 66129c3dd7557cd5ac2fc618ae3bf69f5d60e5f207e81c63bce1c1c65461576e
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