chunk_content: s:
  
  
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  model = get_peft_model(model, peft_config)
  model.print_trainable_parameters()
  "trainable params: 1855499 || all params: 355894283 || trainable%: 0.5213624069370061"
  From the 🤗 Transformers library, create a TrainingArguments class and specify where you want to save the model to, the training hyperparameters, how to evaluate the model, and when to save the checkpoints:
  
  
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  training_args = TrainingArguments(
      output_dir="rob