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BUT-FIT
/
diarizen-wavlm-large-s80-md-v2

Voice Activity Detection
Transformers
PyTorch
speaker
speaker-diarization
meeting
wavlm
wespeaker
diarizen
pyannote
pyannote-audio-pipeline
Model card Files Files and versions
xet
Community
1

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
diarizen-wavlm-large-s80-md-v2 / plda
269 kB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 3 commits
Jyhan003's picture
Jyhan003
docs: add license and README
027b3e2 about 3 hours ago
  • LICENSE
    551 Bytes
    docs: add license and README about 3 hours ago
  • README.md
    518 Bytes
    docs: add license and README about 3 hours ago
  • plda.npz

    Pickle imports

    • No problematic imports detected

    What is a pickle import?

    134 kB
    xet
    feat: initialize diarizen-v2 with 4-overlap speaker setting 9 months ago
  • xvec_transform.npz

    Pickle imports

    • No problematic imports detected

    What is a pickle import?

    134 kB
    xet
    feat: initialize diarizen-v2 with 4-overlap speaker setting 9 months ago