Explaining How to Pay Attention | by Nikolaus Correll | January, 2025

Building a Transformer from scratch to create a simple production model

The Transformer Architecture revolutionized the field of AI and formed the foundation not only for ChatGPT, but also led to unprecedented performance in image recognition, spatial awareness, and robotics. Unfortunately, the design of the transformer itself is complicated, which makes it difficult to see the most important, especially if you are new to machine learning. The best way to understand Transformers is to think of a simple problem like generating random words, character by character. In the previous article, I explained all the tools you will need for such a model, including training models in Pytorch and Batch-Processing, focusing on a very simple model: predicting the next character based on its closure given by the previous character. in a dataset of common words.

In this article, we build on this foundation to present a modern model, the Transformer. We will first provide the basic code to read and process the data, and then introduce the structure of attention by focusing on its main feature first – the cosine similarity between all tokens in a sequence. We'll then add a query, key, and value to create…