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-origin 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-origin with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("BUT-FIT/diarizen-wavlm-large-s80-md-origin", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cdc038770445297f616062463435ee2bdd44f0c4dbf6549f3c21b5cd17392512
- Size of remote file:
- 278 MB
- SHA256:
- 0252b5d926600ad434778a85314f3164601914d36d355cbad3e7e30be968a675
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