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ekhodzitsky/rupunct-small-onnx
rupunct-small-onnx is a token classification model from ekhodzitsky. Use it when you need labels on individual words, such as names. It is set up for onnxruntime. The card lists the license as mit.
INT8-quantized ONNX export of RUPunct/RUPunctsmall (MIT) — Russian punctuation + capitalization restoration as token classification.
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From the Hugging Face model README
INT8-quantized ONNX export of RUPunct/RUPunct_small (MIT) — Russian punctuation + capitalization restoration as token classification.
Packaged for use in the gigastt speech-to-text
server: it runs via ONNX Runtime (no Python at runtime) with the Rust tokenizers
crate, restoring punctuation/casing on the plain rnnt head's bare lowercase output, e.g.
шестьдесят тысяч тенге сколько будет стоить → Шестьдесят тысяч тенге, сколько будет стоить?.
rupunct_small_int8.onnx — dynamic-INT8 graph (DynamicQuantizeLinear + MatMulInteger), ~29 MB.tokenizer.json, config.json, special_tokens_map.json, tokenizer_config.json — HF WordPiece tokenizer + label map (33 labels).input_ids, attention_mask, token_type_ids (int64, [batch, seq]).logits [batch, seq, 33]. Take the first sub-token label per word (aggregation first),
then apply RUPunct's process_token decode (3 case modes × 11 punctuation classes).MIT, inherited from the upstream RUPunct/RUPunct_small. Export + INT8 quantization only; weights are unchanged in accuracy (fp32 and int8 produce identical labels on test inputs).