TF-Keras
TensorBoard
SpeakerRecognition
Fast Fourier Transform (FFT)
Convnet
speech-recordings
SpeechClassification
Instructions to use keras-io/speaker-recognition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use keras-io/speaker-recognition with TF-Keras:
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy), and from_pretrained_keras was removed in huggingface_hub 1.0. # See https://github.com/keras-team/tf-keras for more details. # !pip install "huggingface_hub<1.0" tf_keras from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("keras-io/speaker-recognition") - Notebooks
- Google Colab
- Kaggle
Download keras_metadata.pb from keras-io/speaker-recognition: direct link, hf CLI and curl.
- Browser
- Download file 84.5 kB
-
https://huggingface.co/keras-io/speaker-recognition/resolve/main/keras_metadata.pb
- Command line
-
hf download hf://keras-io/speaker-recognition/keras_metadata.pb
-
curl -L -o keras_metadata.pb https://huggingface.co/keras-io/speaker-recognition/resolve/main/keras_metadata.pb
84.5 kB
- Xet hash:
- 154f23eaee6ead5b1d830fe69a6c881cbe29f8aec8599b7b0d9160cea5d1a046
- Size of remote file:
- 84.5 kB
- SHA256:
- 91cd6a98c4e33f567ebce3eff0ed669f850d16275e0b06c6f106205c4f78b970
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.