code: def create_copy_from_base_model(
      tokenizer: Optional[str] = None,
      vocab: Optional[str] = None,
  ) -> Callable[["Language"], "Language"]:
      def copy_from_base_model(nlp):
          if tokenizer:
              logger.info("Copying tokenizer from: %s", tokenizer)
              base_nlp = load_model(tokenizer)
              if (
                  nlp.config["nlp"]["tokenizer"]
                  == base_nlp.config["nlp"]["tokenizer"]
              ):
                  nlp.tokenizer.from_bytes(
                      base_nlp.tokenizer.to_bytes(exclude=["vocab"])
                  )
              else:
                  raise ValueError(
                      Errors.E872.format(
                          curr_config=nlp.config["nlp"]["tokenizer"],
                          base_config=base_nlp.config["nlp"][
                              "tokenizer"
                          ],
                      )
                  )
          if vocab:
              logger.info("Copying vocab from: %s", vocab)
              # only reload if the vocab is from a different model
              if tokenizer != vocab:
                  base_nlp = load_model(vocab)
              nlp.vocab.from_bytes(base_nlp.vocab.to_bytes())
  
      return copy_from_base_model
  
label_desc: Use image node_id 1 for calling a global function with example usage: create_copy_from_base_model(tokenizer, vocab) and returns: copy_from_base_model