class_docstr: A model wrapper queries a model with a list of text inputs.
  
  Classification-based models return a list of lists, where each
  sublist represents the model's scores for a given input.
  
  Text-to-text models return a list of strings, where each string is
  the output – like a translation or summarization – for a given
  input.
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docstr: Helper method that tokenizes input strings
  Args:
      inputs (list[str]): list of input strings
      strip_prefix (bool): If `True`, we strip auxiliary characters added to tokens as prefixes (e.g. "##" for BERT, "Ġ" for RoBERTa)
  Returns:
      tokens (list[list[str]]): List of list of tokens as strings
docstr_tok: ["Helper","method","that","tokenizes","input","strings","Args",":","inputs","(","list","[","str","]",")",":","list","of","input","strings","strip_prefix","(","bool",")",":","If","`","True","`",",","we","strip","auxiliary","characters","added","to","tokens","as","prefixes","(","e.g",".","``","#","#","''","for","BERT",",","``","\u0120","''","for","RoBERTa",")","Returns",":","tokens","(","list","[","list","[","str","]","]",")",":","List","of","list","of","tokens","as","strings"]
code: def tokenize(self, inputs, strip_prefix=False):
      """Helper method that tokenizes input strings
      Args:
          inputs (list[str]): list of input strings
          strip_prefix (bool): If `True`, we strip auxiliary characters added to tokens as prefixes (e.g. "##" for BERT, "Ġ" for RoBERTa)
      Returns:
          tokens (list[list[str]]): List of list of tokens as strings
      """
      tokens = self._tokenize(inputs)
      if strip_prefix:
          # `aux_chars` are known auxiliary characters that are added to tokens
          strip_chars = ["##", "Ġ", "__"]
          # TODO: Find a better way to identify prefixes. These depend on the model, so cannot be resolved in ModelWrapper.
  
          def strip(s, chars):
              for c in chars:
                  s = s.replace(c, "")
              return s
  
          tokens = [[strip(t, strip_chars) for t in x] for x in tokens]
  
      return tokens
  
imports: from abc import ABC, abstractmethod
label_desc: Use image node_id 4 for calling the ModelWrapper obj's underlying member method code with example usage: obj.tokenize(inputs, strip_prefix) and returns: tokens, s