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:
- 94de61cb578bb83b7636c00798d718783cbef01c3ac13589ee31fac981e73fbc
- Size of remote file:
- 36.5 MB
- SHA256:
- 1ef64781aa03180f4f5ce504314f058f5d0227277df86060473d973cf43b033e
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