Understanding the Weight Averaging Mechanism in LLM Training for Post-Training Quantization
Large language models (LLMs) are typically pretrained in high precision but increasingly deployed with low-precision post-training quantization (PTQ). Recent studies have shown that using weight averaging during pretraining can improve PTQ performance compared with learning-rate decay, suggesting that it might provide...
Han Wang, Tianqi Shen, Zong-Lin Liu et al.
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