code: def word_tokenize(
      sentence, format=None, use_token_normalize=True, fixed_words=[]
  ):
      """
      Vietnamese word segmentation
  
      Args:
          sentence (str): raw sentence
          format (str, optional): format option.
              Defaults to None.
              use format=`text` for text format
          use_token_normalize (bool): True if use token_normalize
          fixed_words (list): list of fixed words
  
      Returns:
          :obj:`list` of :obj:`str`:
              word tokens
  
      Examples:
  
          >>> # -*- coding: utf-8 -*-
          >>> from underthesea import word_tokenize
          >>> sentence = "Bác sĩ bây giờ có thể thản nhiên báo tin bệnh nhân bị ung thư"
  
          >>> word_tokenize(sentence)
          ["Bác sĩ", "bây giờ", "có thể", "thản nhiên", "báo tin", "bệnh nhân", "bị", "ung thư"]
  
          >>> word_tokenize(sentence, format="text")
          "Bác_sĩ bây_giờ có_thể thản_nhiên báo_tin bệnh_nhân bị ung_thư"
      """
      global word_tokenize_model
      tokens = tokenize(
          sentence,
          use_token_normalize=use_token_normalize,
          fixed_words=fixed_words,
      )
      features = [[token] for token in tokens]
      if word_tokenize_model is None:
          word_tokenize_model = FastCRFSequenceTagger()
          wd = dirname(__file__)
          word_tokenize_model.load(
              join(wd, "models", "ws_crf_vlsp2013_20230727")
          )
      tags = word_tokenize_model.predict(features)
  
      output = []
      num_words = 0
      for tag, token in zip(tags, tokens):
          if tag == "I-W" and num_words > 0:
              output[-1] = output[-1] + " " + token
          else:
              output.append(token)
          num_words += 1
      if format == "text":
          output = " ".join([item.replace(" ", "_") for item in output])
      return output
  
imports: from .regex_tokenize import tokenize
  from underthesea.models.fast_crf_sequence_tagger import FastCRFSequenceTagger
  from os.path import dirname, join
label_desc: Use image node_id 1 for calling a global function with example usage: word_tokenize(sentence, format, use_token_normalize, fixed_words) and returns: output