chunk_content: nit="TEXT",
  ...     prompt_tuning_init_text="Predict if sentiment of this review is positive, negative or neutral",
  ...     tokenizer_name_or_path="t5-base",
  ... )
  
  >>> # t5_model.shared is the word embeddings of the base model
  >>> prompt_embedding = PromptEmbedding(config, t5_model.shared)
  Input Shape: (batch_size, total_virtual_tokens)
  Output Shape: (batch_size, total_virtual_tokens, token_dim)
  
  IA3
  	
  
  class peft.IA3Config
  
  <
  source
  >
  (
  peft_