readme:   
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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",
  }
  
  ```
  
  