Heterogeneous Structured Pruning Under Resource Constraints for Hardware-Efficient Large Language Models
Training-free pruning removes weights from pretrained large language models to reduce their deployment cost. However, existing approaches typically consider only the total number of retained weights. Consequently, their pruning decisions do not account for how target hardware stores and processes those weights. These m...
C. Barker, A. Paraskeva, J. V. van Rijn et al.
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