original_docstring: 
  		Displays representative prompt and response terms and utterances for each type learned. 
  
  		:param corpus: corpus to display utterances for (must have `transform()` called on it)
  		:param type_ids: ID of the prompt type to display. if None, will display all types.
  		:param type_key: the name of the prompt type clustering model to use. defaults to `n_types` that the model was initialized with, but if `refit_types` is called with different number of types, can be modified to display this updated model as well.
  		:param k: the number of sample terms (or utteranceS) to display.
  		:return: None
  		
docstring: Displays representative prompt and response terms and utterances for each type learned.
docstring_tokens: Displays representative prompt and response terms and utterances for each type learned .
code: def summarize(self, corpus, type_ids=None, type_key=None, k=10):
  		'''
  		Displays representative prompt and response terms and utterances for each type learned. 
  
  		:param corpus: corpus to display utterances for (must have `transform()` called on it)
  		:param type_ids: ID of the prompt type to display. if None, will display all types.
  		:param type_key: the name of the prompt type clustering model to use. defaults to `n_types` that the model was initialized with, but if `refit_types` is called with different number of types, can be modified to display this updated model as well.
  		:param k: the number of sample terms (or utteranceS) to display.
  		:return: None
  		'''
  		self.pipe.named_steps['pt_model'].summarize(corpus=corpus, type_ids=type_ids, type_key=type_key, k=k)
code_tokens: def summarize ( self , corpus , type_ids = None , type_key = None , k = 10 ) : self . pipe . named_steps [ 'pt_model' ] . summarize ( corpus = corpus , type_ids = type_ids , type_key = type_key , k = k )
short_docstring: Displays representative prompt and response terms and utterances for each type learned.
short_docstring_tokens: Displays representative prompt and response terms and utterances for each type learned .
comment: '''
  		Displays representative prompt and response terms and utterances for each type learned. 
  
  		:param corpus: corpus to display utterances for (must have `transform()` called on it)
  		:param type_ids: ID of the prompt type to display. if None, will display all types.
  		:param type_key: the name of the prompt type clustering model to use. defaults to `n_types` that the model was initialized with, but if `refit_types` is called with different number of types, can be modified to display this updated model as well.
  		:param k: the number of sample terms (or utteranceS) to display.
  		:return: None
  		'''