Marian: Fast neural machine translation in C++. We present Marian, an efficient and self-contained Neural Machine Translation framework with an integrated automatic differentiation engine based on dynamic computation graphs. Marian is written entirely in C++. We describe the design of the encoder-decoder framework and demonstrate that a research-friendly toolkit can achieve high training and translation speed.
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References in zbMATH (referenced in 2 articles )
Showing results 1 to 2 of 2.
- Xiaolin Wang; Masao Utiyama; Eiichiro Sumita: CytonMT: an Efficient Neural Machine Translation Open-source Toolkit Implemented in C++ (2018) arXiv
- Zhiting Hu; Haoran Shi; Zichao Yang; Bowen Tan; Tiancheng Zhao; Junxian He; Wentao Wang; Xingjiang Yu; Lianhui Qin; Di Wang; Xuezhe Ma; Hector Liu; Xiaodan Liang; Wanrong Zhu; Devendra Singh Sachan; Eric P. Xing: Texar: A Modularized, Versatile, and Extensible Toolkit for Text Generation (2018) arXiv
Further publications can be found at: https://marian-nmt.github.io/publications/