chunk_content: Semantic segmentation using LoRA
  	
  This guide demonstrates how to use LoRA, a low-rank approximation technique, to finetune a SegFormer model variant for semantic segmentation.
  By using LoRA from 🤗 PEFT, we can reduce the number of trainable parameters in the SegFormer model to only 14% of the original trainable parameters.
  LoRA achieves this reduction by adding low-rank “update matrices” to specific blocks of the model, such as the attention
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