Let’s Build a Transformer in TensorFlow: Part 1
In this two-part story, we will implement a Transformer model from scratch using TensorFlow. We will go with you through all the steps. Keep Reading.
What is a Transformer?
Transformer is a type of deep learning model, specifically designed for understanding and processing language. It became popular in the field of natural language processing (NLP) due to its unique approach. Unlike older methods that process information step-by-step, transformers use a special technique called “attention” to focus on the most relevant parts of the input. This allows them to handle various NLP tasks, such as translation and text generation, more effectively.
Inside the Transformer
The Transformer is like a machine with two parts: an encoder and a decoder. They work together to understand and create sequences of text. The encoder acts like a “reader” — it takes in the text and gets a general idea of its meaning. Then, the decoder acts like a “writer” — it uses what the encoder learned to create a new piece of text, following the same rules as the original.
The key to how Transformers work is something called “attention.” Imagine you’re reading a document — with attention, the Transformer can focus on specific parts of the text that are most…