Transformer Explained

A Transformer is a model architecture that eschews recurrence and instead relies entirely on an attention mechanism to draw global dependencies between input and output. Before Transformers, the dominant sequence transduction models were based on complex recurrent or convolutional neural networks that include an encoder and a decoder. The Transformer also employs an encoder and decoder, but removing recurrence in favor of attention mechanisms allows for significantly more parallelization than methods like RNNs and CNNs.

Generative pre-trained transformer - Wikipedia

What is a Transformer (And How Does it Work)?

Visualizing and Explaining Transformer Models From the Ground Up - Deepgram Blog ⚡️

Transformer Basics and Transformer Principles

Transformer's Self-Attention Mechanism Simplified

Transformers Explained Visually (Part 1): Overview of Functionality, by Ketan Doshi

How A Transformer Works: How it Works Jameco Electronics

Detection Transformer (DETR) Explained : r/neuralnetworks

Transformers Explained Visually (Part 1): Overview of Functionality, by Ketan Doshi

Universal Transformer Explained

What is a Transformer? Beginner's Guide

Transformer Cooling Systems and Methods Explained - Articles - TestGuy Electrical Testing Network

What is Transformer? Explain its Working Principle.

Illustrated Guide to Transformers- Step by Step Explanation, by Michael Phi