Модели-ученики
material
ID: studentmodels
Related Papers
Speed-optimized, Compact Student Models that Distill Knowledge from a Larger Teacher Model: the UEDIN-CUNI Submission to the WMT 2020 News Translation Task
AbstractWe describe the joint submission of the University of Edinburgh and Charles University, Prague, to the Czech/English track in the WMT 2020 Shared Task on News Translation. Our fast and …...
Improving Zero-Shot Multilingual Text Generation via Iterative Distillation
AbstractThe demand for multilingual dialogue systems often requires a costly labeling process, where human translators derive utterances in low resource languages from resource rich language annotation. To this end, we …...
Sparse Distillation: Speeding Up Text Classification by Using Bigger Student Models
AbstractDistilling state-of-the-art transformer models into lightweight student models is an effective way to reduce computation cost at inference time. The student models are typically compact transformers with fewer parameters, while …...