chunk_content: atrices in a neural network to reduce the number of trainable
  parameters. However, for simplicity and further parameter efficiency, in Transformer models LoRA is typically applied to
  attention blocks only. The resulting number of trainable parameters in a LoRA model depends on the size of the low-rank
  update matrices, which is determined mainly by the rank r and the shape of the original weight matrix.
  
  Merge LoRA weights into the base model
  	
  