pyannote.audio
PyTorch
TensorBoard
pyannote
pyannote-audio-model
audio
voice
speech
speaker
speaker-recognition
speaker-verification
speaker-identification
speaker-embedding
Instructions to use dereklvlv/embedding with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- pyannote.audio
How to use dereklvlv/embedding with pyannote.audio:
from pyannote.audio import Model, Inference model = Model.from_pretrained("dereklvlv/embedding") inference = Inference(model) # inference on the whole file inference("file.wav") # inference on an excerpt from pyannote.core import Segment excerpt = Segment(start=2.0, end=5.0) inference.crop("file.wav", excerpt) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 167e4a153cc7c155c1e813fe94059a6e2c165cc83129b7494a0996f2917efcd3
- Size of remote file:
- 96.4 MB
- SHA256:
- 4bcec986de13da7af7ac88736572692359950df63669989c4f78b294934c9089
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.