chunk_content: LoRA 
  	
  This conceptual guide gives a brief overview of LoRA, a technique that accelerates
  the fine-tuning of large models while consuming less memory. 
  To make fine-tuning more efficient, LoRA’s approach is to represent the weight updates with two smaller
  matrices (called update matrices) through low-rank decomposition. These new matrices can be trained to adapt to the
  new data while keeping the overall number of changes low. The original weig