text: from sparknlp.annotator import *
  
  class WordSegmenter:
      @staticmethod
      def get_default_model():
          return WordSegmenterModel()\
              .setInputCols(["document"]) \
              .setOutputCol("token")
  
  
      @staticmethod
      def get_pretrained_model(name, language):
          return WordSegmenterModel.pretrained(name,language) \
              .setInputCols(["document"]) \
              .setOutputCol("token")
  
      @staticmethod
      def get_default_model_for_lang(language):
          name = WordSegmenter.get_default_word_seg_for_lang(language)
  
          return WordSegmenterModel.pretrained(name,language) \
              .setInputCols(["document"]) \
              .setOutputCol("token")
  
  
      @staticmethod
      def get_default_word_seg_for_lang(language):
          import nlu
          # get default reference
          return nlu.NameSpace.pretrained_models_references[language][language+'.'+'segment_words']