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| license: mit |
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| license: mit |
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| **Model Description** |
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| 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 |
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| **How to Translate with this Model** |
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| + 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-arg 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-arg input.bpe > output.txt |
| ``` |
| ```bash |
| sed -i 's/@@ //g' output.txt |
| ``` |
| **Funding** |
| This model was developed within the Nós Project, funded by the Ministerio para la Transformación Digital y de la Función Pública - Funded by EU – NextGenerationEU within the framework of the [project ILENIA] (https://proyectoilenia.es/) with reference 2022/TL22/00215336. |
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| ## Citation |
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| 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. |
