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Related Questions
- How does knowledge distillation affect the number of parameters in a transformer model's attention heads?
- Can knowledge distillation be used to reduce the memory footprint of a transformer model without sacrificing its accuracy?
- Are there any trade-offs between knowledge distillation and the number of attention heads in a transformer model?
- How does the number of attention heads impact the memory requirements of a transformer model, and can knowledge distillation mitigate this?
- Can knowledge distillation be combined with other techniques to further reduce the memory requirements of a transformer model's attention heads?
- Are there any specific architecture changes that can be made to a transformer model to reduce the memory requirements of its attention heads using knowledge distillation?
- How does the level of knowledge distillation (hard, soft, or temperature-based) impact the reduction in memory requirements of attention heads in a transformer model?
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