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Determining the Number of Attention Heads
In a multi-head attention mechanism, the input representation has a dimension of 768. The weight matrix used to compute the 'key' vector for a single attention head has a shape of . Assuming the total dimension of the 'key' projection across all heads is equal to the input representation dimension, how many attention heads are being used? Explain your reasoning.
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Ch.2 Generative Models - Foundations of Large Language Models
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In a neural network component, an input representation of dimension 512 is processed by 8 parallel 'heads'. For each head, a 'key' vector is produced by multiplying the input representation by a specific weight matrix. The dimensions of the 'key' vectors from all heads are concatenated, resulting in a final combined dimension of 512. What is the shape of the weight matrix used to produce the 'key' vector for a single head?
Determining the Number of Attention Heads
Debugging a Multi-Head Attention Layer