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:
- 7c562dde31ebe9d4b575b632e3d8490d8dcc8d6bc42f3bd10c1cc9dacdf784fc
- Size of remote file:
- 166 MB
- SHA256:
- 9f54389d63cc36864d14fb5c6a1b542a3c046ee5c58e44588cde27904c2a8a02
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