What is
Attention Mechanism?
The transformer component that lets each token in a sequence attend to other tokens.
Definition
Attention computes weighted relationships between every pair of tokens in a sequence. This is what gives transformers their long-range reasoning ability. Multi-head attention runs many attention computations in parallel, each learning different relational patterns. Modern variants (FlashAttention, sparse attention) make attention computationally tractable on long sequences.
Example
In "The cat sat on the mat because it was tired," attention helps the model link "it" to "cat" rather than "mat."
How Vedwix uses Attention Mechanism in client work
Conceptual; rarely something we tune directly except in custom-trained models.
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