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---
license: mit
---
---
license: mit
---
**Descrici贸n do Modelo**
Modelo feito con OpenNMT para o par espa帽ol-galego utilizando unha arquitectura transformer.
**Como utilizar**
+ Abrir terminal bash
+ Instalar [Python 3.9](https://www.python.org/downloads/release/python-390/)
+ Instalar [Open NMT toolkit v.2.2](https://github.com/OpenNMT/OpenNMT-py)
+ Traducir un input_text utilizando o modelo NOS-MT-en-gl co seguinte comando:
```bash
onmt_translate -src input_text聽-model NOS-MT-es-gl -output ./output_file.txt -replace_unk -phrase_table phrase_table-es-gl.txt -gpu 0
```
+ O resultado da traduci贸n estar谩 no PATH indicado no flag -output.
**Adestramento**
Datos utilizados para o adestramento
Aut茅nticos e Sint茅ticos (Translitera莽茫o)[Colocar Paper]
**Procedemento de adestramento**
Tokenization feita co tokenizador de linguakit https://github.com/citiususc/Linguakit
BPE
**Hiperpar谩metros**
Colocar o yaml para cada um dos pares
**Avaliaci贸n**
A avalaci贸n dos modelos 茅 feita cunha mistura de tests desenvolvidos internamente
(gold1, gold2, test-suite) con outros datasets dispon铆beis en galego (Flores).
| GOLD 1 | GOLD 2 | FLORES | TEST-SUITE|
| ------------- |:-------------:| -------:|----------:|
| 36.8 | 47.1 | 32.3 | 42.7 |
**Informaci贸n adicional**
Licensing information
Apache License, Version 2.0
**Financiamento**
Financiamento
This research was funded by the project "N贸s: Galician in the society and economy of artificial intelligence", agreement between Xunta de Galicia and University of Santiago de Compostela, and grant ED431G2019/04 by the Galician Ministry of Education, University and Professional Training, and the European Regional Development Fund (ERDF/FEDER program), and Groups of Reference: ED431C 2020/21.
**Citation Information**
@article{,
title={},
author={},
year={2022},
url={}
} |