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:
- 24151063bf8015a16592bbf6e4eaa59601c2c66bd2575e6d641ffa993f49bb31
- Size of remote file:
- 66.9 MB
- SHA256:
- a793fa34ed2174f5229601c9dc31b92bdf4802c6c5b9e6f299cf958873932eda
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