pyannote-speaker-diarization-3.1 (Vokra GGUF)

Converted to the Vokra GGUF format for Vokra, a zero-dependency speech-AI inference runtime.

This is a conversion, not a new model. The weights are the upstream ones; Vokra re-packages them so its runtime can memory-map them directly. Credit for the model belongs upstream — see Source below.

Files

File	Size	SHA-256
pyannote-speaker-diarization-3.1.gguf	0.0 MB	6f2fe6d681d75fdde84768792f54725baf4e5e025f3a9c4af9618867a64e3a64

Usage

# Download (any HTTP client works — the file is a plain GGUF)
curl -L -o pyannote-speaker-diarization-3.1.gguf \
  https://huggingface.co/vokra/pyannote-speaker-diarization-3.1/resolve/main/pyannote-speaker-diarization-3.1.gguf

vokra-cli run --model pyannote-speaker-diarization-3.1.gguf --input input.wav

Provenance

Field	Value
Architecture	pyannote-speaker-diarization
Tensors	0
Upstream source	pyannote/speaker-diarization-3.1 (SpeakerDiarization pipeline: segmentation-3.0 VAD + wespeaker-voxceleb-resnet34-LM embedding + AgglomerativeClustering, MIT)
Upstream licence	mit
Licence class	permissive
Registry model id	pyannote-speaker-diarization-3.1
Vokra GGUF schema	1
Converted by	vokra-core 0.1.0-alpha.0

Every row above is read out of this file's own vokra.* metadata, so the card cannot claim something the artifact does not carry.

Licence

The weights are distributed under mit, unchanged from upstream. Conversion does not alter the licence, and your obligations run to the upstream author.

Verifying this file

shasum -a 256 pyannote-speaker-diarization-3.1.gguf
# expect: 6f2fe6d681d75fdde84768792f54725baf4e5e025f3a9c4af9618867a64e3a64