gector-roberta-onnx

GECToR RoBERTa base (5k) — ONNX export

ONNX exports of gotutiyan/gector-roberta-base-5k, packaged for Silent Voice, a local-first dictation app for Windows. It runs the model on CPU through ONNX Runtime to underline grammar mistakes as you type.

⚠️ Licence — non-commercial only

The upstream model card for gotutiyan/gector-roberta-base-5k states:

Only non-commercial purposes.

That restriction carries over to these files. They are a format conversion of those weights, not a new model, so this repo cannot grant broader rights than the original. Do not use them commercially.

Note that Silent Voice itself is MIT-licensed. That covers the application code only — this model is an optional download with its own terms, and is not bundled with the app.

Credit

• GECToR: Omelianchuk, Atrasevych, Chernodub & Skurzhanskyi, GECToR – Grammatical Error Correction: Tag, Not Rewrite (BEA 2020) — https://aclanthology.org/2020.bea-1.16/
• This checkpoint is an unofficial reimplementation by gotutiyan.

Variants

Supporting files, needed by either variant:

Signature

inputs   input_ids       [batch, sequence]  int64
         attention_mask  [batch, sequence]  int64
outputs  label_logits    [batch, sequence, 5001]
         detect_logits   [batch, sequence, 2]

labels.txt is ordered to match the label_logits axis, index 0 being <OOV> and index 1 $KEEP. Detection classes are $CORRECT (0) and $INCORRECT (1).

Reproducing

Exported with gector-work/export_gector.py in the Silent Voice repo: torch.onnx.export for the FP32 graph, then onnxruntime.quantization.quantize_dynamic(weight_type=QUInt8) for the INT8 build.