all AI news
AutoDistill: An End-to-End Fully Automated Distillation Framework for Hardware-Efficient Large-Scale NLP Models
Jan. 26, 2022, 3:44 p.m. | Synced
Synced syncedreview.com
University of Illinois Urbana-Champaign and Google researchers introduce AutoDistill, an end-to-end fully automated model distillation framework that integrates model architecture exploration and multi-objective optimization for building hardware-efficient pretrained natural language processing models.
The post AutoDistill: An End-to-End Fully Automated Distillation Framework for Hardware-Efficient Large-Scale NLP Models first appeared on Synced.
ai artificial intelligence automl distillation framework hardware machine learning machine learning & data science ml model distillation nlp pretrained language model research scale technology
More from syncedreview.com / Synced
Jobs in AI, ML, Big Data
AI Research Scientist
@ Vara | Berlin, Germany and Remote
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne
Data Science Analyst
@ Mayo Clinic | AZ, United States
Sr. Data Scientist (Network Engineering)
@ SpaceX | Redmond, WA