preprint Open access

Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling

  • arXiv (Cornell University)
  • Cornell University
Research footprint

At a glance

Citations
184
References
3
Comments
0
Paper overview

Abstract

Lingvo is a Tensorflow framework offering a complete solution for collaborative deep learning research, with a particular focus towards sequence-to-sequence models. Lingvo models are composed of modular building blocks that are flexible and easily extensible, and experiment configurations are centralized and highly customizable. Distributed training and quantized inference are supported directly within the framework, and it contains existing implementations of a large number of utilities, helper functions, and the newest research ideas. Lingvo has been used in collaboration by dozens of researchers in more than 20 papers over the last two years. This document outlines the underlying design of Lingvo and serves as an introduction to the various pieces of the framework, while also offering examples of advanced features that showcase the capabilities of the framework.

Record transparency

Publication details

DOI
10.48550/arxiv.1902.08295
OpenAlex
W2928941594
Document type
preprint
Language
EN
Source
arXiv (Cornell University)
Last metadata update
Community

Comments

Log in to join the discussion.

  1. No comments yet. Start the discussion.