Abstract
We present Sockeye 2, a modernized and streamlined version of the Sockeye neural machine translation (NMT) toolkit. New features include a simplified code base through the use of MXNet’s Gluon API, a focus on state of the art model architectures, and distributed mixed precision training. These improvements result in faster training and inference, higher automatic metric scores, and a shorter path from research to production.- Anthology ID:
- 2020.eamt-1.50
- Volume:
- Proceedings of the 22nd Annual Conference of the European Association for Machine Translation
- Month:
- November
- Year:
- 2020
- Address:
- Lisboa, Portugal
- Editors:
- André Martins, Helena Moniz, Sara Fumega, Bruno Martins, Fernando Batista, Luisa Coheur, Carla Parra, Isabel Trancoso, Marco Turchi, Arianna Bisazza, Joss Moorkens, Ana Guerberof, Mary Nurminen, Lena Marg, Mikel L. Forcada
- Venue:
- EAMT
- SIG:
- Publisher:
- European Association for Machine Translation
- Note:
- Pages:
- 457–458
- Language:
- URL:
- https://aclanthology.org/2020.eamt-1.50
- DOI:
- Cite (ACL):
- Felix Hieber, Tobias Domhan, Michael Denkowski, and David Vilar. 2020. Sockeye 2: A Toolkit for Neural Machine Translation. In Proceedings of the 22nd Annual Conference of the European Association for Machine Translation, pages 457–458, Lisboa, Portugal. European Association for Machine Translation.
- Cite (Informal):
- Sockeye 2: A Toolkit for Neural Machine Translation (Hieber et al., EAMT 2020)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2020.eamt-1.50.pdf
- Code
- awslabs/sockeye