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Related Questions
- Can you explain how multi-head attention combines the output from multiple attention heads into a single vector?
- How does the multiple attention heads in the decoder allow the model to look at different parts of the input sequence?
- What are the computational and memory implications of the multiple attention heads, compared to a single head model?
- Does multi-head attention affect the interpretability of the attention mechanism, and why or why not?
- Can you explain the effect of the hyperparameters that control the number and size of the attention heads?
- What are the implications of having a large number of attention heads on the performance and generalizability of the model?
- Can you discuss the limitations and potential drawbacks of multi-head attention, and suggest any alternative approaches?
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