Jun Yao
2021
HW-TSC’s Participation in the WMT 2021 Efficiency Shared Task
Hengchao Shang
|
Ting Hu
|
Daimeng Wei
|
Zongyao Li
|
Jianfei Feng
|
ZhengZhe Yu
|
Jiaxin Guo
|
Shaojun Li
|
Lizhi Lei
|
ShiMin Tao
|
Hao Yang
|
Jun Yao
|
Ying Qin
Proceedings of the Sixth Conference on Machine Translation
This paper presents the submission of Huawei Translation Services Center (HW-TSC) to WMT 2021 Efficiency Shared Task. We explore the sentence-level teacher-student distillation technique and train several small-size models that find a balance between efficiency and quality. Our models feature deep encoder, shallow decoder and light-weight RNN with SSRU layer. We use Huawei Noah’s Bolt, an efficient and light-weight library for on-device inference. Leveraging INT8 quantization, self-defined General Matrix Multiplication (GEMM) operator, shortlist, greedy search and caching, we submit four small-size and efficient translation models with high translation quality for the one CPU core latency track.
Search
Co-authors
- Hengchao Shang 1
- Ting Hu 1
- Daimeng Wei 1
- Zongyao Li 1
- Jianfei Feng 1
- show all...
Venues
- wmt1