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
docs: add license and README
Browse files- plda/{LICENSE.LICENSE → LICENSE} +0 -0
- plda/README.md +1 -1
plda/{LICENSE.LICENSE → LICENSE}
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These files are licensed under the Creative Commons Attribution 4.0
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International License (CC BY 4.0), which permits commercial use.
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See [`LICENSE`](LICENSE) for the license terms.
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Copyright (c) Brno University of Technology / BUT Speech@FIT.
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These files are licensed under the Creative Commons Attribution 4.0
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International License (CC BY 4.0), which permits commercial use.
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See [`LICENSE`](https://huggingface.co/BUT-FIT/diarizen-wavlm-large-s80-md-v2/blob/main/plda/LICENSE) for the license terms.
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Copyright (c) Brno University of Technology / BUT Speech@FIT.
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