---
library_name: ctranslate2
pipeline_tag: translation
license: apache-2.0
base_model: protonx-models/protonx-legal-tc
language:
  - vi
tags:
  - ctranslate2
  - ct2
  - text2text-generation
  - vietnamese
  - ocr-correction
  - post-ocr
  - distillation
---

# Distilled protonx-legal-tc — CTranslate2 (Vietnamese OCR text correction)

Distilled + CTranslate2-converted version of [`protonx-models/protonx-legal-tc`](https://huggingface.co/protonx-models/protonx-legal-tc) for fast CPU OCR text correction on Vietnamese administrative documents.

The original protonx-legal-tc is a seq2seq model trained for legal-text correction. This distilled CT2 build is optimized for CPU inference and used by the [ScanIndex](https://github.com/welcomyou/scanindex) pipeline as the correction stage between OCR and PDF/DOCX export.

## Performance (ScanIndex internal benchmark)

| Variant | Time / 13 pages | Accuracy |
|---|---|---|
| protonx-legal-tc (CT2 OPTIMIZE, beam=1) | 14.5s | 99.561% |
| **This distilled CT2 (beam=1)**         | **8.3s** | **99.550%** |

42% faster, 0.011 pp accuracy drop — recommended trade-off for CPU.

## Files

- `distilled_ct2/model.bin` — CTranslate2 model
- `distilled_ct2/tokenizer.json`, `tokenizer_config.json`, `special_tokens_map.json`, `shared_vocabulary.json`, `config.json`

## Loading

```python
import ctranslate2
from transformers import AutoTokenizer
from huggingface_hub import snapshot_download

local = snapshot_download("welcomyou/distilled-protonx-vn-correction-ct2", local_dir="models")
sub = f"{local}/distilled_ct2"
translator = ctranslate2.Translator(sub, device="cpu")
tok = AutoTokenizer.from_pretrained(sub)
```

## License

Apache-2.0, inheriting from the protonx-legal-tc base.