 opus-mt-tc-base-uk-ro  Neural machine translation model for translating from Ukrainian (uk) to Romanian (ro).  This model is part of the [OPUS-MT project](https://github.com/Helsinki-NLP/Opus-MT), an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of [Marian NMT](https://marian-nmt.github.io/), an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from [OPUS](https://opus.nlpl.eu/) and training pipelines use the procedures of [OPUS-MT-train](https://github.com/Helsinki-NLP/Opus-MT-train).  * Publications: [OPUS-MT – Building open translation services for the World](https://aclanthology.org/2020.eamt-1.61/) and [The Tatoeba Translation Challenge – Realistic Data Sets for Low Resource and Multilingual MT](https://aclanthology.org/2020.wmt-1.139/) (Please, cite if you use this model.)  ``` @inproceedings{tiedemann-thottingal-2020-opus,     title = "{OPUS}-{MT} {--} Building open translation services for the World",     author = {Tiedemann, J{\"o}rg  and Thottingal, Santhosh},     booktitle = "Proceedings of the 22nd Annual Conference of the European Association for Machine Translation",     month = nov,     year = "2020",     address = "Lisboa, Portugal",     publisher = "European Association for Machine Translation",     url = "https://aclanthology.org/2020.eamt-1.61",     pages = "479--480", }  @inproceedings{tiedemann-2020-tatoeba,     title = "The Tatoeba Translation Challenge {--} Realistic Data Sets for Low Resource and Multilingual {MT}",     author = {Tiedemann, J{\"o}rg},     booktitle = "Proceedings of the Fifth Conference on Machine Translation",     month = nov,     year = "2020",     address = "Online",     publisher = "Association for Computational Linguistics",     url = "https://aclanthology.org/2020.wmt-1.139",     pages = "1174--1182", } ```  