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 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 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("BUT-FIT/diarizen-wavlm-large-s80-md", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Minor update: add metadata and LFS tracking
Browse files- .gitattributes +1 -0
- README.md +2 -0
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README.md
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---
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license: mit
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tags:
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- speaker
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- speaker-diarization
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license: mit
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pipeline_tag: speaker-diarization
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library_name: custom
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tags:
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- speaker
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- speaker-diarization
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