Instructions to use kozy9/GWTCN with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use kozy9/GWTCN with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://kozy9/GWTCN") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 912879518d0bd404fa789a47d1837a0dd6ffff92b46da26539385034413b866d
- Size of remote file:
- 394 kB
- SHA256:
- c744ba7ea03d6719a9c3c8fa1cc6d2f9a52b7d5c8f6a187adff9ab75593a62d6
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