juniorLLMs

What is a Transformer architecture?

Updated May 16, 2026

Short answer

A Transformer is a neural network architecture based on self-attention mechanisms.

Deep explanation

Transformers replace recurrence with self-attention, allowing models to process all tokens in parallel. They consist of encoder and decoder stacks with multi-head attention and feed-forward layers. This architecture enables better long-range dependency handling compared to RNNs.

Real-world example

Google Translate uses transformer models for translation tasks.

Common mistakes

Thinking transformers process text sequentially like RNNs.

Follow-up questions

What is self-attention?
Why transformers replaced RNNs?

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