chunk_content: pied
  peft_config = PromptEncoderConfig(task_type="SEQ_CLS", num_virtual_tokens=20, encoder_hidden_size=128)
  Create the base roberta-large model from AutoModelForSequenceClassification, and then wrap the base model and peft_config with get_peft_model() to create a PeftModel. If you’re curious to see how many parameters you’re actually training compared to training on all the model parameters, you can print it out with print_trainable_parameters(