File size: 1,525 Bytes
0515c38 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 |
---
language:
- en
tags:
- gec
library_name: opennmt
license: mit
metrics:
- bleu
inference: false
---
### Introduction
This repository contains a description on how to use OpenNMT on the Grammar Error Correction (GEC) task. The idea is to approch GEC as a translation task
### Usage
Install the necessary dependencies:
```bash
pip3 install ctranslate2 pyonmttok
```
Simple tokenization & translation using Python:
```python
import ctranslate2
import pyonmttok
from huggingface_hub import snapshot_download
model_dir = snapshot_download(repo_id="jordimas/gec-opennmt-english", revision="main")
tokenizer=pyonmttok.Tokenizer(mode="none", sp_model_path = model_dir + "/sp_m.model")
tokenized=tokenizer.tokenize("The water are hot. My friends are going to be late. Today mine mother is in Barcelona.")
translator = ctranslate2.Translator(model_dir)
translated = translator.translate_batch([tokenized[0]])
print(tokenizer.detokenize(translated[0][0]['tokens']))
```
# Model
The model has been training using the [clang8](https://github.com/google-research-datasets/clang8) corpus for English language.
Details:
* Model: TransformerBase
* Tokenizer: SentencePiece
* BLEU = 85.50
# Papers
Relevant papers:
* [Approaching Neural Grammatical Error Correction as a Low-Resource Machine Translation Task](https://aclanthology.org/N18-1055.pdf)
* [A Simple Recipe for Multilingual Grammatical Error Correction](https://arxiv.org/pdf/2106.03830.pdf)
# Contact
Email address: Jordi Mas: jmas@softcatala.org
|