chunk_content: p guide on how to train a model with prefix tuning.
  
  P-tuning
  	
  
  Prompt tokens can be inserted anywhere in the input sequence, and they are optimized by a prompt encoder (image source).
  P-tuning is designed for natural language understanding (NLU) tasks and all language models.
  It is another variation of a soft prompt method; P-tuning also adds a trainable embedding tensor that can be optimized to find better prompts, and it uses a prompt encod