Transformer Decoder - Pretraining and Finetuning

Learn about the fundamental concepts of Transformer decoders, including their pretraining and finetuning processes in this comprehensive lecture from the University of Utah's Data Science program. Dive deep into the architecture and mechanisms that make transformer decoders powerful tools in natural language processing and machine learning applications. Explore the two-stage approach of pretraining and finetuning, understanding how these models can be adapted for various downstream tasks while leveraging knowledge gained from large-scale pretraining.