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Related Questions
- How does the number of attention heads affect the model's capacity to learn complex relationships between input tokens?
- Can you explain the impact of increasing the number of attention heads on the model's ability to generalize to out-of-distribution data?
- How does the attention head architecture influence the model's ability to capture long-range dependencies in the input data?
- What is the optimal number of attention heads for a given model architecture and dataset?
- Can you discuss the trade-off between increasing the number of attention heads and the model's computational efficiency?
- How does the number of attention heads relate to the model's ability to learn hierarchical representations of the input data?
- Can you provide examples of how different numbers of attention heads can affect the model's performance on specific tasks, such as language translation or question answering?
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