chunk_content: lize a base model from AutoModelForCausalLM, and pass it and peft_config to the get_peft_model() function to create a PeftModel. You can print the new PeftModel’s trainable parameters to see how much more efficient it is than training the full parameters of the original model!
  
  
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  model = AutoModelForCausalLM.from_pretrained(model_name_or_path)
  model = get_peft_model(model, peft_config)
  print(model.print_trainable_parameters())
  "trainable