Papers › ViNMT: Neural Machine Translation Toolkit

ViNMT: Neural Machine Translation Toolkit

31 Dec 2021arXiv:2112.15272archive 2025-07-28

Nguyen Hoang Quan, Nguyen Thanh Dat, Nguyen Hoang Minh Cong, Nguyen Van Vinh, Ngo Thi Vinh, Nguyen Phuong Thai, Tran Hong Viet

We present an open-source toolkit for neural machine translation (NMT). The new toolkit is mainly based on vaulted Transformer (Vaswani et al., 2017) along with many other improvements detailed below, in order to create a self-contained, simple to use, consistent and comprehensive framework for Machine Translation tasks of various domains. It is tooled to support both bilingual and multilingual translation tasks, starting from building the model from respective corpora, to inferring new predictions or packaging the model to serving-capable JIT format.

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Code

kcdichdangu/multilingualmt-uet-kc4.0 officialmentioned in papermentioned on GitHubpytorch report

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Tasks

Machine Translation NMT Translation

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Methods

Absolute Position Encodings Adam Attention BPE Dense Connections Dropout Label Smoothing Layer Normalization Linear Layer Multi-Head Attention Position-Wise Feed-Forward Layer Residual Connection Softmax Transformer

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