chunk_content: CLS, inference_mode=False, r=16, lora_alpha=16, lora_dropout=0.1, bias="all"
  )
  Pass the base model and peft_config to the get_peft_model() function to create a PeftModel. You can check out how much more efficient training the PeftModel is compared to fully training the base model by printing out the trainable parameters:
  
  
  	Copied
  model = get_peft_model(model, peft_config)
  model.print_trainable_parameters()
  "trainable params: 1855499 || all par