Understanding LLMs
Lesson 3 of 6
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Lesson 3
45 min

The Transformer Architecture

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Quick Summary

Self-attention lets every token in a sequence look at every other token at once and decide which ones matter. That single idea, scaled up, is the engine inside every modern LLM.

What you will learn
  • ·Understand how the Transformer's attention mechanism works conceptually
  • ·Explain why attention solved the long-range dependency problem
  • ·Understand multi-head attention and what it adds