chunk_content: m_pretrained(model_name_or_path)
  model = get_peft_model(model, peft_config)
  print(model.print_trainable_parameters())
  "trainable params: 8192 || all params: 559222784 || trainable%: 0.0014648902430985358"
  Setup an optimizer and learning rate scheduler:
  
  
  	Copied
  optimizer = torch.optim.AdamW(model.parameters(), lr=lr)
  lr_scheduler = get_linear_schedule_with_warmup(
      optimizer=optimizer,
      num_warmup_steps=0,
      num_training_steps=(len(tra