efer to the discussion on this PR. 
Low-Rank Adaptation of Large Language Models (LoRA) is a training method that accelerates the training of large models while consuming less memory. It adds pairs of rank-decomposition weight matrices (called update matrices) to existing weights, and only trains those newly added weights. This has a couple of advantages:
Previous pretrained weights are kept frozen so the model is not as prone to catastrophic f