What is attention mechanism in transformer models and how does it differ from RNNs for sequence modeling?

Data Science with Python Hard

Data Science with Python — Hard

What is attention mechanism in transformer models and how does it differ from RNNs for sequence modeling?

Key points

  • Attention computes relationships in parallel, RNNs process sequentially
  • Attention has O(1) path length, RNNs suffer from long-range dependency issues
  • Attention uses scaled dot-product weights, RNNs do not
  • Attention allows for more efficient sequence modeling compared to RNNs

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