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Related Questions
- What is the role of attention heads in self-attention mechanisms and how do they contribute to capturing complex relationships?
- How does the number of attention heads impact the model's capacity to learn contextual relationships between input elements?
- Can you explain the trade-off between increasing the number of attention heads and model complexity, and how it affects performance?
- How does the self-attention mechanism with multiple attention heads compare to other contextual representation methods in terms of capturing long-range dependencies?
- What are the implications of using a large number of attention heads on the model's computational requirements and memory usage?
- Can you discuss the relationship between the number of attention heads and the model's ability to generalize to unseen data?
- How does the number of attention heads affect the model's ability to capture nuanced relationships between input elements, such as those involving negation or implication?
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