This lecture covers:
1. A brief note on subword modeling
2. Motivating model pretraining from word embeddings
3. Model pretraining three ways
1. Decoders
2. Encoders
3. Encoder-Decoders
4. Interlude: what do we think pretraining is teaching?
5. Very large models and in-context learning
To learn more about this course visit: https://online.stanford.edu/courses/c…
To follow along with the course schedule and syllabus visit: http://web.stanford.edu/class/cs224n/
John Hewitt
https://nlp.stanford.edu/~johnhew/
Professor Christopher Manning
Thomas M. Siebel Professor in Machine Learning, Professor of Linguistics and of Computer Science
Director, Stanford Artificial Intelligence Laboratory (SAIL)
#naturallanguageprocessing #deeplearning
Add comment