Instructions to use csukuangfj/moonshine-fork with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use csukuangfj/moonshine-fork with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://csukuangfj/moonshine-fork") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7605ae35650cf47dcad0464a5e5103b1ae9719254921a0f4fe8ec549d80b4a61
- Size of remote file:
- 24.2 MB
- SHA256:
- a35b4b5907c0757bf080a95878bd4af7024b7f4041cf85e694d057b4187d7011
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