original_docstring: 
  			for a particular prompt type, displays the representative prompt and response terms. can also display representative prompt and response utterances.
  
  			:param type_id: ID of the prompt type to display.
  			:param corpus: pass in the training corpus to also display representative utterances.
  			: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: for a particular prompt type, displays the representative prompt and response terms. can also display representative prompt and response utterances.
docstring_tokens: for a particular prompt type displays the representative prompt and response terms . can also display representative prompt and response utterances .
code: def display_type(self, type_id, corpus=None, type_key=None, k=10):
  		"""
  			for a particular prompt type, displays the representative prompt and response terms. can also display representative prompt and response utterances.
  
  			:param type_id: ID of the prompt type to display.
  			:param corpus: pass in the training corpus to also display representative utterances.
  			: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'].display_type(type_id, corpus=corpus, type_key=type_key, k=k)
code_tokens: def display_type ( self , type_id , corpus = None , type_key = None , k = 10 ) : self . pipe . named_steps [ 'pt_model' ] . display_type ( type_id , corpus = corpus , type_key = type_key , k = k )
short_docstring: for a particular prompt type, displays the representative prompt and response terms.
short_docstring_tokens: for a particular prompt type displays the representative prompt and response terms .
comment: """
  			for a particular prompt type, displays the representative prompt and response terms. can also display representative prompt and response utterances.
  
  			:param type_id: ID of the prompt type to display.
  			:param corpus: pass in the training corpus to also display representative utterances.
  			: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
  
  		"""