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What is attention in Transformer models?

Attention is how, for each token, a model decides how much to look at every other token in context. The result mixes values so related words can receive higher weight.

Transformers often use multi-head attention — several “heads” that can learn different relationship types.

mej7.com provides illustrative attention maps and Q/K/V sections for intuition — not measurements from a production model.

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