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Generative Language Model Pruning

1 post · Aug 2026

What this trail covers

IDEA Prune introduces an integrated enlarge-and-prune pipeline for generative language model pretraining. It combines enlarged model pretraining, pruning, and recovery under a single cosine annealing learning rate schedule, complemented by an iterative structured pruning method for gradual parameter removal. This approach mitigates knowledge loss and facilitates smooth compression and enhanced performance, achieving superior performance of pruned models.

All Apple trails
  1. IDEA Prune: An Integrated Enlarge-and-Prune Pipeline in Generative Language Model PretrainingThis post proposes an integrated enlarge-and-prune pipeline for generative language model pretraining, combining enlarged model training, pruning, and recovery under a single cosine annealing learning rate schedule. It also introduces an iterative structured pruning method for gradual parameter removal to mitigate knowledge loss and enable effective redistribution of model capacity, leading to superior performance of pruned models.