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-mlc 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-mlc with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("BUT-FIT/diarizen-wavlm-large-s80-mlc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 675f8c61775016d5585d129bcec12df4d85130b63b9ce1835118804b6b68d4de
- Size of remote file:
- 278 MB
- SHA256:
- 9117101fefd61c74201edac55a47418f9137d6381fcc327db9cb9b780551a93d
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