Agents

Attention Mechanism

1 min read

What It Means

The core innovation in transformers that allows models to weigh the relevance of different parts of the input.

Attention enables models to focus on relevant context regardless of position, key to handling long sequences.

How It Works

  • Query-key-value computation
  • Attention weights computed
  • Weighted combination of values
  • Multi-head for different aspects

Significance

  • Enables long-range dependencies
  • Parallelizable (unlike RNNs)
  • Foundation of modern LLMs
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