The answer
Because it relates positions of a single sequence to calculate a representation of the same sequence.
Because it relates positions of a single sequence to calculate a representation of the same sequence.
An attention calculation that divides scores by the square root of the vector dimension to prevent gradients from exploding.
Global attention looks at all words in the input, while local attention only looks at a sliding window of neighboring words.
Yes, Vision Transformers (ViTs) apply self-attention to image patches instead of text tokens.
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