Instructions to use said1447/speaker-recognition-cnn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use said1447/speaker-recognition-cnn with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://said1447/speaker-recognition-cnn") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 20998aadf6580db0fe51a86855da381214b5c25d503851cc28c80d259abd2cfc
- Size of remote file:
- 18.3 MB
- SHA256:
- 51c292478d94ec3a01461bdfa82eb0885d262eb09e615679b2d69dedb6ad09e7
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