README.md

metadata

license: mit
language:
  - ru
library_name: onnxruntime
pipeline_tag: token-classification
tags:
  - punctuation
  - capitalization
  - russian
  - onnx
  - int8

scribe-punct-ru

Russian punctuation + capitalization models for Scribe offline voice dictation, exported to ONNX and quantized to int8 for CPU inference.

The repo hosts two model sizes. Scribe downloads the one listed in its punct_models.json catalog, into models/punct/ru/.

Models

Model	Files	Size	Speed (CPU)	Notes
RUPunct_big (BERT-base)	rupunct_big_int8.onnx, rupunct_big_tokenizer.json, rupunct_big_model.json	~178 MB	~15 ms per phrase	Best quality; default in the Scribe catalog
RUPunct_small	rupunct_small_int8.onnx, tokenizer.json, model.json	~29 MB	~1–3 ms per phrase	Lightweight alternative, kept for compatibility

Both models share the same 33-label scheme (case of this word + mark after it), so the same decoding code in Scribe works for both. The sidecar *_model.json is the Scribe label map and decoding style description.

Label scheme

33 classes: case of this word (UPPER / LOWER / TOTAL) + mark after it (PERIOD, COMMA, QUESTION, TIRE, VOSKL, DVOETOCHIE, PERIODCOMMA, DEFIS, QUESTIONVOSKL, MNOGOTOCHIE, O).

Usage in Scribe

Downloaded by Scribe's model manager into models/punct/ru/, runs fully offline via ONNX Runtime. No torch / transformers needed at runtime.

License / attribution

MIT.

• RUPunct_big: base model RUPunct/RUPunct_big; fp32 ONNX export by IcPlus/rupunct-onnx (MIT); dynamic int8 quantization is a format conversion only, weights were not retrained.
• RUPunct_small: export of ekhodzitsky/rupunct-small-onnx (MIT), converted from RUPunct/RUPunct_small.

Scribe sidecars (model.json, rupunct_big_model.json) and this card are MIT as well.