docstr: Checks if the given token is a part of the tail of a word. Note that a word can
  be split in multiple tokens (e.g., ``word = [head_token tail_token_1 tail_token_2 ... tail_token_k]``).
  Each language model has a convention on how to mark a tail token. For example
  `DistilbertBaseUncased` and `BertBaseUncased` have the tail tokens prefixed with the special
  set of characters ``'##'``. On the other hand, for `RobertaBase` only the head token is prefixed
  with the special character ``'Ġ'`` and thus we need to check the absence of the prefix to identify
  the tail tokens. We call those special characters `SUBWORD_PREFIX`. Due to different conventions,
  this method has to be implemented for each language model. See module docstring for namings.
  
  Parameters
  ----------
  token
      Token to be checked if it is a subword.
  
  Returns
  -------
  ``True`` if the given token is a subword prefix. ``False`` otherwise.
docstr_tok: ["Checks","if","the","given","token","is","a","part","of","the","tail","of","a","word",".","Note","that","a","word","can","be","split","in","multiple","tokens","(","e.g.",",","``","word","=","[","head_token","tail_token_1","tail_token_2","...","tail_token_k","]","``",")",".","Each","language","model","has","a","convention","on","how","to","mark","a","tail","token",".","For","example","`","DistilbertBaseUncased","`","and","`","BertBaseUncased","`","have","the","tail","tokens","prefixed","with","the","special","set","of","characters","``","'","#","#","'","``",".","On","the","other","hand",",","for","`","RobertaBase","`","only","the","head","token","is","prefixed","with","the","special","character","``","'","\u0120","'","``","and","thus","we","need","to","check","the","absence","of","the","prefix","to","identify","the","tail","tokens",".","We","call","those","special","characters","`","SUBWORD_PREFIX","`",".","Due","to","different","conventions",",","this","method","has","to","be","implemented","for","each","language","model",".","See","module","docstring","for","namings",".","Parameters","--","--","--","--","--","token","Token","to","be","checked","if","it","is","a","subword",".","Returns","--","--","--","-","``","True","``","if","the","given","token","is","a","subword","prefix",".","``","False","``","otherwise","."]
code: def is_subword_prefix(self, token: str) -> bool:
      """
      Checks if the given token is a part of the tail of a word. Note that a word can
      be split in multiple tokens (e.g., ``word = [head_token tail_token_1 tail_token_2 ... tail_token_k]``).
      Each language model has a convention on how to mark a tail token. For example
      `DistilbertBaseUncased` and `BertBaseUncased` have the tail tokens prefixed with the special
      set of characters ``'##'``. On the other hand, for `RobertaBase` only the head token is prefixed
      with the special character ``'Ġ'`` and thus we need to check the absence of the prefix to identify
      the tail tokens. We call those special characters `SUBWORD_PREFIX`. Due to different conventions,
      this method has to be implemented for each language model. See module docstring for namings.
  
      Parameters
      ----------
      token
          Token to be checked if it is a subword.
  
      Returns
      -------
      ``True`` if the given token is a subword prefix. ``False`` otherwise.
      """
      pass
  
imports: import abc
  import numpy
  from pathlib import Path
  from typing import Any, Callable, List, Optional, Tuple, Union
  import tensorflow
  import transformers
  from transformers import TFAutoModelForMaskedLM, AutoTokenizer
label_desc: Use image node_id 4 for calling the LanguageModel obj's underlying member method code with example usage: obj.is_subword_prefix(token) without return types