| --- |
| license: mit |
| base_model: PalabraAI/redimnet2 |
| pipeline_tag: feature-extraction |
| library_name: openasr |
| tags: |
| - speaker-diarization |
| - openasr |
| - oasr |
| --- |
| |
| <div align="center"> |
|
|
| # ReDimNet2-B6 Speaker Embedder (CN-enhanced) · OpenASR |
|
|
| **ReDimNet2-B6 speaker embedder for OpenASR diarization — 192-d CN-enhanced embeddings, fully on-device** |
|
|
| [](https://github.com/PalabraAI/redimnet2/blob/main/LICENSE) |
| [](https://github.com/QuintinShaw/openasr) |
| [](https://openasr.org) |
| [](https://huggingface.co/PalabraAI/redimnet2) |
|
|
| Speaker-diarization support pack for the **[OpenASR](https://github.com/QuintinShaw/openasr)** runtime — |
| pure-Rust inference, **no Python at inference time**. |
|
|
| </div> |
|
|
| --- |
|
|
| ## ✨ Highlights |
|
|
| - 🗣️ **OpenASR speaker embedder** — the only supported speaker-embedding pack for diarization and Voice ID; required for anonymous speaker labels on any ASR family |
| - 🧬 **192-dim ReDimNet2-B6** — PalabraAI's dimension-reshaping speaker net (12.5M params) with a Chinese-enhanced vb2+vox2+cnc2 training mix |
| - 🔒 **Diarization, not identification** — anonymous session-relative labels; embeddings stay local and are discarded after the request unless you explicitly enroll a local profile |
| - 🎯 **Parity-gated packaging** — ggml-graph forward pass matches the upstream Python reference at cosine ≥ 0.9999 on held-out fixtures |
| - 🦀 **Native in OpenASR** — `.oasr` packs run with no Python at inference, engineered for peak performance on CPU & GPU |
|
|
| ## 🚀 Quickstart |
|
|
| ```bash |
| # 1. Install the OpenASR CLI · https://openasr.org |
| # 2. Pull the pack |
| openasr pull redimnet2-b6-cn:fp16 |
| |
| # 3. Diarize any transcription (works with every OpenASR ASR model) |
| openasr transcribe meeting.wav --model xasr-zh-en --diarize --format srt |
| ``` |
|
|
| ## 📦 Pack |
|
|
| | Quant | File (`.oasr`) | Size | |
| |:------|:---------------|-----:| |
| | fp16 | `redimnet2-b6-cn-fp16.oasr` | 28 MB | |
|
|
| <sub>Single **fp16** build: projection weights ship as fp16; norms/biases and other |
| parity-sensitive tensors stay f32 inside the pack. No extra public quant tiers.</sub> |
|
|
| ## 🧠 About ReDimNet2-B6 Speaker Embedder (CN-enhanced) |
|
|
| ReDimNet2-B6 is PalabraAI's 12.5M-parameter speaker-embedding model from the |
| ReDimNet2 family, trained on a VoxBlink2 + VoxCeleb2 + CN-Celeb2 mix so English and |
| Chinese speakers share one embedding space. OpenASR packages the MIT-licensed |
| checkpoint as a local `.oasr` capability pack and runs it through a ggml graph |
| (not a pure-Rust hand-written forward). This is the only supported speaker-embedding |
| stage for diarization and Voice ID: when the pack is missing, diarize/Voice ID |
| requests fail closed rather than falling back to another embedder. Embeddings are |
| 192-d cosine vectors with a ReDimNet-specific calibration profile. |
|
|
| ## ⚙️ How this pack was made |
|
|
| Converted from [PalabraAI/redimnet2](https://huggingface.co/PalabraAI/redimnet2) with the OpenASR importer: |
|
|
| ```bash |
| openasr model-pack import redimnet2 <src>.safetensors <out>.oasr \ |
| --package-id redimnet2-b6-cn |
| ``` |
|
|
| The `.oasr` container is GGUF-backed; projection weights are stored as fp16 while |
| norms/biases and other parity-sensitive tensors remain f32. |
|
|
| ## ⚖️ License |
|
|
| This pack **inherits the upstream model's license: MIT** |
| ([source](https://github.com/PalabraAI/redimnet2/blob/main/LICENSE)). OpenASR packaging retains the upstream copyright; |
| the only modification is format conversion. |
|
|
| ## 🙏 Acknowledgements |
|
|
| This pack redistributes **PalabraAI/redimnet2** checkpoint |
| `b6-vb2+vox2+cnc2_v0-lm.pt` in OpenASR's `.oasr` runtime format. Credit for the |
| model architecture, training, and original weights belongs to the upstream |
| PalabraAI / ReDimNet2 authors (paper: ReDimNet2: Scaling Speaker Verification via |
| Time-Pooled Dimension Reshaping). The upstream model is licensed under **MIT**; |
| OpenASR packaging retains that license and attribution, with the only modification |
| being format conversion for local ggml-graph loading. |
|
|
| ## 🔗 Links |
|
|
| - 🦀 **OpenASR** — <https://github.com/QuintinShaw/openasr> |
| - 🌐 **Website** — <https://openasr.org> |
| - 🤗 **Upstream model** — [PalabraAI/redimnet2](https://huggingface.co/PalabraAI/redimnet2) |
|
|
