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Related Questions
- What is the primary difference in data requirements between knowledge distillation and model pruning?
- How does knowledge distillation affect the amount of data needed for training a compressed model compared to model pruning?
- Can you explain the trade-offs between data requirements and model performance in knowledge distillation versus model pruning?
- How does the choice of knowledge distillation or model pruning impact the need for large-scale datasets?
- What are the implications of using knowledge distillation versus model pruning on the amount of data required for training a compressed model?
- Can you provide a comparison of the data requirements for knowledge distillation and model pruning in terms of the number of samples and computational resources?
- How does the compression ratio achieved by knowledge distillation compare to that of model pruning in terms of data efficiency?
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