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Related Questions
- What is the purpose of the attention mechanism in a transformer model, and how do attention heads contribute to it?
- How do different attention heads in a multi-head attention mechanism interact and cooperate with each other during the processing of input sequences?
- Can you explain the concept of attention head diversity in transformer models and its impact on model performance?
- What are some common pitfalls or issues associated with using multiple attention heads in a transformer model, and how can they be addressed?
- How do attention heads learn to specialize in different aspects of the input data, and what factors influence this specialization?
- In what scenarios is it beneficial to use multiple attention heads, and when is it more effective to use a single attention head?
- Can you discuss the trade-offs between increasing the number of attention heads and the model's computational complexity and training time?
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