Update README.md

README.md

@@ -1,3 +1,30 @@
----
-license: mit
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+---
+license: mit
+---
+**Model Description** 
+
+Model created with OpenNMT-py 3.2 for the Spanish-Aragonese pair using a transformer architecture. The model was converted to the ctranslate2 format.
+This model was trained for the paper Training and fine-tuning NMT models for low-resource languages using Apertium-based synthetic corpora
+
+**How to Translate with this Model**
+
++ Install [Python 3.9](https://www.python.org/downloads/release/python-390/) 
++ Install [ctranslate 3.2](https://github.com/OpenNMT/CTranslate2)
++ Translate an input_text using the NOS-MT-es-arn model with the following command:
+```bash
+    perl tokenizer.perl < input.txt > input.tok
+```
+```bash
+    subword_nmt.apply_bpe -c ./bpe/es.bpe < input.tok > input.bpe
+```
+```bash 
+    python3 translate.py ./ct2-arn input.bpe > output.txt
+```
+```bash
+    sed -i 's/@@ //g' output.txt
+```
+
+## Citation
+
+If you use this model in your research, please cite the following paper:
+Sant, A., Bardanca Outeiriño, D., Pichel Campos, J. R., De Luca Fornaciari, F., Escolano, C., García Gilabert, J., Gamallo Otero, P., Mash, A., Liao, X., & Melero, M. (2023). Training and fine-tuning NMT models for low-resource languages using Apertium-based synthetic corpora. arXiv.