In the context of transformers, which factor is most crucial for scaling self-attention to large datasets?
Question
In the context of transformers, which factor is most crucial for scaling self-attention to large datasets?
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Solution 1
In the context of transformers, the most crucial factor for scaling self-attention to large datasets is the computational complexity.
Here's a step-by-step explanation:
- Transformers use self-attention mechanism, which allows them to consider the entire input sequence simultaneously and weigh t Knowee AI StudyGPT is a powerful AI-powered study tool designed to help you to solve study prob
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