code: def add_special_tokens_(
      model,
      tokenizer,
      attr_to_special_token,
  ) -> None:
      orig_num_tokens = len(tokenizer)
      num_added_tokens = tokenizer.add_special_tokens(
          attr_to_special_token  # type: ignore
      )  # doesn't add if they are already there
      if num_added_tokens > 0:
          model.resize_token_embeddings(
              new_num_tokens=orig_num_tokens + num_added_tokens
          )
  
file_path: speechbrain/recipes/MultiWOZ/response_generation/llama2/train_with_llama2.py
imports: import sys
  import speechbrain
  import torch
  from itertools import chain
  from hyperpyyaml import load_hyperpyyaml
  from speechbrain.utils.distributed import run_on_main
  import math
  from speechbrain.dataio.batch import PaddedBatch
label_desc: Use image node_id 1 for calling a global function with example usage: add_special_tokens_(model, tokenizer, attr_to_special_token) without return types