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.
The Transformer Model
What is a Transformer (And How Does it Work)?
Ideal Transformer - Explained with Schematics and equations
Electrical Transformer Explained - The Engineering Mindset
Current Transformers (CTs) Explained - Continental Control Systems, LLC
What is a Transformer? Transformers Explained - Working Principle ( Transformer Tutorial)
Transformer's Self-Attention Mechanism Simplified
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Transformer Ultimate Guide
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Transformer - Wikipedia
Transformers Tutorial (Paper Explained + Implementation in Tensorflow and Pytorch) - Part1 🤗⚡
Transformer Tap Changers: Basic Principles and Testing Explained - Articles - TestGuy Electrical Testing Network
Visualizing and Explaining Transformer Models From the Ground Up - Deepgram Blog ⚡️
