The Annotated Transformer

The Annotated Transformer

———————- There is now a new version of this blog post updated for modern PyTorch. ———————- from IPython.display import Image Image ( filename = 'images/aiayn.png' ) The Transformer from “Attention is All You Need” has been on a lot of people’s minds over the last year. Besides producing major improvements in translation quality, it provides a new architecture for many other NLP tasks. The paper itself is very clearly written, but the conventional wisdom has been that it is quite difficult to implement correctly. In this post I present an “annotated” version of the paper in the form of a line-b

saved by

• HudZah
• Jasroop Dhingra
• Tera Minato
• Cheikh Fiteni

related reading

• The Annotated Transformernlp.seas.harvard.edu
• The Illustrated Transformer – Jay Alammar – Visualizing machine learning one concept at a time.jalammar.github.io
• transformer_attention.pdfarxiv.org
• The Annotated Transformernlp.seas.harvard.edu
• Transformers from Scratche2eml.school
• The Illustrated Transformer – Jay Alammar – Visualizing machine learning one concept at a time.jalammar.github.io
• Transformers Laid Outgoyalpramod.github.io
• A Mathematical Framework for Transformer Circuitstransformer-circuits.pub
• Transformers from scratch | peterbloem.nlpeterbloem.nl
• 1706.03762arxiv.org
• Attention is all you need: Discovering the Transformer paper | Towards Data Sciencetowardsdatascience.com
• Let's build GPT: from scratch, in code, spelled out.youtube.com