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Related Questions
- How does increasing the number of attention heads affect the model's ability to capture contextual relationships?
- What are the primary trade-offs between increasing the number of attention heads and model complexity?
- How does the increased computational cost of more attention heads impact model training time and resource requirements?
- Can you discuss the relationship between the number of attention heads and model performance on tasks that require capturing long-range dependencies?
- How do the trade-offs between attention heads and model complexity change as the model's architecture and training data evolve?
- What are some strategies for balancing the number of attention heads and model complexity to achieve optimal performance?
- How does the choice of attention head architecture (e.g., multi-head, multi-scale) impact the trade-offs between model complexity and performance?
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