pytorch t5 text2text-generation arxiv:2206.03933 transformers autotrain_compatible
  
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    <img src="https://github.com/UBC-NLP/turjuman/raw/master//images/turjuman_logo.png"/>
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  <img src="https://github.com/UBC-NLP/turjuman/raw/master/images/turjuman.png" alt="AraT5" width="50%" height="50%" align="right"/>



Turjuman is a neural machine translation toolkit. It translates from 20 languages into Modern Standard Arabic (MSA). Turjuman is described in this paper: 
[**TURJUMAN: A Public Toolkit for Neural Arabic Machine Translation**](https://arxiv.org/abs/2206.03933).

Turjuman exploits our [AraT5 model](https://github.com/UBC-NLP/araT5). This endows Turjuman with a powerful ability to decode into Arabic. The toolkit offers the possibility of employing a number of diverse decoding methods, making it suited for acquiring paraphrases for the MSA translations as an added value.


**Github**: [https://github.com/UBC-NLP/turjuman](https://github.com/UBC-NLP/turjuman)

**Demo**: [https://demos.dlnlp.ai/turjuman](https://demos.dlnlp.ai/turjuman)

**Paper**: [https://arxiv.org/abs/2206.03933](https://arxiv.org/abs/2206.03933)

## License
turjuman(-py) is Apache-2.0 licensed. The license applies to the pre-trained models as well.

## Citation
If you use TURJUMAN toolkit or the pre-trained models for your scientific publication, or if you find the resources in this repository useful, please cite our paper as follows (to be updated):
```
@inproceedings{nagoudi-osact5-2022-turjuman,
  title={TURJUMAN: A Public Toolkit for Neural Arabic Machine Translation},
  author={Nagoudi, El Moatez Billah and Elmadany, AbdelRahim and Abdul-Mageed, Muhammad},
  booktitle = "Proceedings of the 5th Workshop on Open-Source Arabic Corpora and Processing Tools (OSACT5)",
  month = "June",
  year = "2022",
  address = "Marseille, France",
  publisher = "European Language Resource Association",
}

```

