Instructions to use littlebearlabs/witness-pyannote-seg-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use littlebearlabs/witness-pyannote-seg-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir witness-pyannote-seg-mlx littlebearlabs/witness-pyannote-seg-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
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license: mit
library_name: mlx
tags:
- mlx
- speaker-diarization
- witness
---
# witness-pyannote-seg-mlx
`pyannote/segmentation-3.0` powerset speaker segmentation, converted to a
gate-free MLX safetensors for witness's on-device speaker diarization.
## Upstream attribution
- **Model**: pyannote `segmentation-3.0` (PyanNet powerset segmentation).
- **Authors / source**: pyannote — `pyannote/segmentation-3.0`.
- **License**: MIT (the segmentation-3.0 model weights are MIT-licensed).
## What's in this repo
- `model.safetensors` — gate-free converted weights produced by
`.research/diarization/gen_seg_fixture.py`. Validated to 100% per-frame
powerset-argmax agreement with the upstream export (logits max_abs ≈ 2.5e-5).
---
*Converted to MLX for [witness](https://github.com/littlebearlabs/witness), an
open-source Rust toolkit for on-device system capture on macOS. Generated by
`.research/diarization/publish_weights.sh`.*
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