The Illustrated Transformer

A closer look at The Illustrated Transformer

What The Illustrated Transformer is

This is a long, illustrated walkthrough of the Transformer model (from the paper "Attention is All You Need"). The post explains the model’s main components - encoder and decoder stacks, self-attention, feed-forward layers and how tensors flow through the model - with diagrams and step-by-step exposition. The page also links to related resources like a Tensor2Tensor notebook for interactive visualization and notes that the post has been expanded into a book chapter and a free short course with animations.

What you can actually do on the page

Read a conceptual, example-driven explanation of how the Transformer works, including how embeddings, queries/keys/values and self-attention are computed and why the architecture enables parallelization. Follow links to implementations (Tensor2Tensor) and an interactive notebook to load and inspect a Transformer model. Find translations in many languages and pointers to lectures and courses that reference the post.

Who will find this useful

Students and practitioners who want an intuitive, visual introduction to the Transformer and self-attention without deep prior exposure to the original paper will benefit most. Instructors can use it as course material (it’s noted as featured in several university courses), and anyone who wants a guided path from high-level concepts to vector/matrix calculations and runnable notebooks should find it helpful.

Questions people ask about The Illustrated Transformer

Does the page link to runnable code?

Yes, it links to a Tensor2Tensor implementation and an interactive notebook to load and examine a Transformer model.

Is the content available in other languages?

Yes, the post has multiple translations listed, including Arabic, Chinese, French, Italian, Japanese, Korean, Persian, Russian, Spanish and Vietnamese.

Does the page cover practical training or deployment details?

It discusses how the Transformer enables parallelization and points to implementations and resources, but the page is primarily an explanatory walkthrough rather than a step-by-step deployment guide.

The Illustrated Transformer was shared on NexURLs by Nexis on October 27, 2026, in Tech & AI.