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Related Questions
- What are the key differences between model pruning and weight pruning in the context of pre-trained language models?
- How does knowledge distillation impact the pruning process for pre-trained language models, and what are its benefits?
- Can you explain the concept of adaptive pruning and its application in fine-tuning pre-trained language models?
- What are the trade-offs between model size and performance when pruning pre-trained language models, and how can they be optimized?
- How do techniques such as magnitude-based pruning, threshold-based pruning, and frequency-based pruning compare in terms of effectiveness and computational efficiency?
- What role does regularization play in the pruning process for pre-trained language models, and how can it be tuned for optimal results?
- Can you discuss the impact of pruning on the interpretability of pre-trained language models, and how can it be addressed?
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