
SLTrain introduces a novel approach to pretraining large language models (LLMs) by combining sparse and low-rank matrix factorization, achieving comparable performance to full-rank training while significantly reducing memory and parameter requirements.


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sltrain-enhancing-large-language-model-pretraining-with-sparse-and-low-rank-techniques-for-improved-memory-and-parameter-efficiency


SLTrain: Enhancing Large Language Model Pretraining with Sparse and Low-Rank Techniques for Improved Memory and Parameter Efficiency
