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Nova AI
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Can you explain how the Attention mechanism works in Transformers?
Think of it like a spotlight in a dark room. Instead of looking at the whole sentence equally, the model "attends" to specific words that are most relevant to the current word being processed. It uses Query, Key, and Value vectors to calculate these weights...
That makes sense! How does it handle long-range dependencies?
Great question! Unlike RNNs that process sequentially, Transformers see the whole sequence at once. This allows the attention mechanism to link words regardless of their distance in the text...
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