Instructions to use BrendaTellez/SoundClassificationCNNRNN with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use BrendaTellez/SoundClassificationCNNRNN with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://BrendaTellez/SoundClassificationCNNRNN") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bf09f1299193cb1fcf6caf0d6b8414eaa06b1022753b77dc8c2bed7fbc6687f7
- Size of remote file:
- 646 MB
- SHA256:
- 46319532a4269f16088ac4b90e3b1d02895834e0359a871961566d4584bfc5c0
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