Instructions to use nixsng/benign_keras with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use nixsng/benign_keras with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://nixsng/benign_keras") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9f3b3954aa5860d5c17df060c08bf0892df4cd6a4be121900c50b0981abcd9f8
- Size of remote file:
- 167 MB
- SHA256:
- b1ae0ef9419474ace5c9895d12dbba8450b32d190baa8001904dc4247580bfc2
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