File size: 1,356 Bytes
df169b5 b9c9a3b 9c371d1 b9c9a3b |
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 |
---
license: cc-by-nc-sa-4.0
language:
- hu
- en
tags:
- translation
- opennmt
inference: false
---
### Introduction
Hungarian - English translation model that was trained on the [Hunglish2](http://mokk.bme.hu/resources/hunglishcorpus/) dataset using OpenNMT.
### 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="SZTAKI-HLT/opennmt-hu-en", revision="main")
tokenizer=pyonmttok.Tokenizer(mode="none", sp_model_path = model_dir + "/sp_m.model")
tokenized=tokenizer.tokenize("Hello világ")
translator = ctranslate2.Translator(model_dir)
translated = translator.translate_batch([tokenized[0]])
print(tokenizer.detokenize(translated[0].hypotheses[0]))
```
## Citation
If you use our model, please cite the following paper:
```
@inproceedings{nagy2022syntax,
title={Syntax-based data augmentation for Hungarian-English machine translation},
author={Nagy, Attila and Nanys, Patrick and Konr{\'a}d, Bal{\'a}zs Frey and Bial, Bence and {\'A}cs, Judit},
booktitle = {XVIII. Magyar Számítógépes Nyelvészeti Konferencia (MSZNY 2022)},
year={2022},
publisher = {Szegedi Tudományegyetem, Informatikai Intézet},
}
``` |