Seq2Seq

Seq2Seq is a general-purpose encoder-decoder framework for Tensorflow that can be used for Machine Translation, Text Summarization, Conversational Modeling, Image Captioning, and more.

Keywords for this software

Anything in here will be replaced on browsers that support the canvas element

References in zbMATH (referenced in 3 articles , 1 standard article )

Showing results 1 to 3 of 3.
Sorted by year (citations)

  1. Oleksii Kuchaiev; Boris Ginsburg; Igor Gitman; Vitaly Lavrukhin; Carl Case; Paulius Micikevicius: OpenSeq2Seq: extensible toolkit for distributed and mixed precision training of sequence-to-sequence models (2018) arXiv
  2. Xiaolin Wang; Masao Utiyama; Eiichiro Sumita: CytonMT: an Efficient Neural Machine Translation Open-source Toolkit Implemented in C++ (2018) arXiv
  3. Denny Britz, Anna Goldie, Minh-Thang Luong, Quoc Le: Massive Exploration of Neural Machine Translation Architectures (2017) arXiv