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Consider a simplified attention mechanism in a transformer-based NLP model. Given the following vectors: . Query Vector (Q): Q-[0.3,-0.1,0.4]Q=[0.3,-0.1,0.4] Key Vectors (K): . K=[[0.2,0.5,-0.3],[0.4,-0.2,0.1],[-0.1,0.3,0.6]]K-[[0.2,0.5,-0.3],[0.4,-0.2,0.1],[-0.1,0.3,0.6]]
Consider a simplified attention mechanism in a transformer-based NLP model. Given the following vectors: . Query Vector (Q): Q-[0.3,-0.1,0.4]Q=[0.3,-0.1,0.4] Key Vectors (K): . K=[[0.2,0.5,-0.3],[0.4,-0.2,0.1],[-0.1,0.3,0.6]]K-[[0.2,0.5,-0.3],[0.4,-0.2,0.1],[-0.1,0.3,0.6]] Value Vectors (V): V=[[1,0,0], [0,1,0], [0,0,1]]V=[[1,0,0],[0,1,0],[0,0,1]] Calculate the attention scores for the given query vector Q. Clearly show your calculations.
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