Instructions to use hzhongresearch/yamnetp_ahead_ds with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use hzhongresearch/yamnetp_ahead_ds with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://hzhongresearch/yamnetp_ahead_ds") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e2c91de4c28c9b618b415da285e89350d4bd9a38026b381051f956da0f9c3f05
- Size of remote file:
- 489 kB
- SHA256:
- d76b73b0138b3db478c8c9c4d543ea7026e4dddc36cbd81d499233272a5907f3
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