Voice Activity Detection
Transformers
PyTorch
speaker
speaker-diarization
meeting
wavlm
wespeaker
diarizen
pyannote
pyannote-audio-pipeline
Instructions to use BUT-FIT/diarizen-wavlm-large-s80-md-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BUT-FIT/diarizen-wavlm-large-s80-md-v2 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("BUT-FIT/diarizen-wavlm-large-s80-md-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e5f31c78169dc3916a8aac05d8daa83705d7659515c5b34780edf09c3e5b9594
- Size of remote file:
- 134 kB
- SHA256:
- 9b77bcd840692710dd3496f62ecfeed8d8e5f002fd991b785079b244eab7d255
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