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:
- f64dc3b8aed670e3975ce33a446e21a8e9a5b5ed5fcec6c2fa01c0ce5402d7dd
- Size of remote file:
- 78 MB
- SHA256:
- 2f36805f4a7ebf29a2598fa26b6a964882e2f0403658126403d04e52e61eece5
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