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Related Questions
- What are the primary benefits of using multiple attention heads in transformer architectures?
- How does the number of attention heads affect the computational cost of a model?
- What is the ideal number of attention heads to balance performance and efficiency in a typical NLP task?
- How does increasing the number of attention heads impact model capacity and training time?
- Can you provide a formula or metric to quantify the trade-off between model performance and computational cost?
- What are some common techniques used to reduce the computational cost of models with multiple attention heads?
- How does the number of attention heads interact with other hyperparameters, such as sequence length and batch size, to impact model performance and efficiency?
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