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Related Questions
- What are the key differences in computational complexity between self-attention and recurrence in transformer models?
- How does the use of self-attention in transformer models compare to the use of recurrence in RNNs in terms of computational complexity?
- Can you explain the trade-offs between the increased computational complexity of self-attention and its benefits in transformer models?
- What are some strategies for reducing the computational complexity of self-attention in transformer models?
- How does the use of self-attention in transformer models impact the training time and memory requirements compared to RNNs?
- Can you provide an example of how self-attention and recurrence compare in terms of computational complexity for a specific NLP task?
- What are the implications of the increased computational complexity of self-attention for the deployment of transformer models in real-world applications?
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