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yap-diarize-models
wilsonguenther/yap-diarize-models
yap-diarize-models is a machine learning model from wilsonguenther. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as other.
This repository is a byte-for-byte mirror of two upstream sherpa-onnx release assets. Nothing here is re-exported, re-quantized or re-packaged: the files are uploaded exactly as the upstream release serves them, so th…
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Updated Aug 15, 2026
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.onnx29.3 MB · 81%
At a glance
- License
- other
- Access
- Public
- Created
- Aug 15, 2026
- Updated
- Aug 15, 2026
- SHA
- c0f5026b
Model card
From the Hugging Face model README
yap-diarize-models — Yap's pinned diarization model mirror
This repository is a byte-for-byte mirror of two upstream sherpa-onnx release assets. Nothing here is re-exported, re-quantized or re-packaged: the files are uploaded exactly as the upstream release serves them, so their sha256 digests match the upstream digests.
It exists so that Yap's
models.rs catalog can pin a revision + sha256 it controls, instead of
downloading vendor release archives directly at runtime.
| File | Bytes | sha256 | Upstream |
|---|---|---|---|
sherpa-onnx-pyannote-segmentation-3-0.tar.bz2 | 6,958,444 | 24615ee884c897d9d2ba09bb4d30da6bb1b15e685065962db5b02e76e4996488 | k2-fsa/sherpa-onnx speaker-segmentation-models |
wespeaker_en_voxceleb_CAM++.onnx | 29,292,684 | c46fad10b5f81e1aa4a60c162714208577093655076c5450f8c469e522ec54ef | k2-fsa/sherpa-onnx speaker-recongition-models (upstream tag typo is upstream's) |
Licenses (unchanged by mirroring)
- pyannote/segmentation-3.0 — MIT (
LICENSEinside the archive, © 2022 CNRS). The model card states it will remain open-source. The archive also carries anmodel.int8.onnxquantized sibling and the upstream export scripts; Yap loadssherpa-onnx-pyannote-segmentation-3-0/model.onnx(5,992,913 bytes, sha256220ad67ca923bef2fa91f2390c786097bf305bceb5e261d4af67b38e938e1079). - wespeaker_en_voxceleb_CAM++ — WeSpeaker toolkit is Apache-2.0; the VoxCeleb-derived weights are CC-BY-4.0. 192-dimensional embeddings.
Rev's sherpa-onnx-reverb-diarization-v{1,2} models are deliberately not
mirrored here: they are released for non-commercial use only, which is
incompatible with a paid product.
- License
- other
- Created
- Aug 15, 2026
- Updated
- Aug 15, 2026