Visualizing Attention in Transformers Self-attention mechanisms, such as those used in Transformers, use Key-Query-Value (KQV) pairs to relate words. When processing a sequence of tokens, each token is represented by three vectors: a query, a key, and a value The query vector of a token is compared to the key vectors of all other tokens, using a similarity score (often dot product). This score determines how much attention (or importance) one token should give to another This way, each token can
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