README.md

---
pipeline_tag: translation
library_name: transformers
---

### Biomedical French to English Neural Machine Translation

<u>Source language:</u> fr  
<u>Target language:</u> en  
<u>Training dataset:</u> WMT20, Cochrane bilingual parallel corpus, Taus Corona Crisis corpus, Mlia Covid corpus  
<u>Development set:</u> Medline 18, Medline 19  
<u>Test set:</u> Medline 20  
<u>Model:</u> transformer  
<u>Pre-processing:</u> SentencePiece  

## Benchmark

<div style="width: 20%; text-align: left;">

| **Test set**   | **BLEU** |
|----------------|----------|
| Medline20      | 35.8     |

</div>

## How to use this Model?
* This model can be accessed via git clone:
  ```
  git clone https://huggingface.co/SLPG/Biomedical_French_to_English
  ```
* You can use Fairseq library to access the model for translations:
  ```
  from fairseq.models.transformer import TransformerModel
  ```
* Load the model
  ```
  model = TransformerModel.from_pretrained('path/to/model')
  ```
* Set the model to evaluation mode
  ```
  model.eval()
  ```
* Perform inference
  ```
  input_text = 'Hello, how are you?'
  output_text = model.translate(input_text)
  print(output_text)
  ```

## Citation

**If you use our model, kindly cite our [paper](https://hal.science/hal-03430610/document)**:
```
  @inproceedings{xu2021lisn,
  title={LISN@ WMT 2021},
  author={Xu, Jitao and Rauf, Sadaf Abdul and Pham, Minh Quang and Yvon, Fran{\c{c}}ois},
  booktitle={6th Conference on Statistical Machine Translation},
  year={2021}
  }
```