original_docstring: 
  			infers a different number of prompt types than was originally called.
  
  			:param n_types: number of types to learn
  			:param random_state: random seed
  			:param name: the name of the new type model. defaults to n_types.
  			:return: None
  		
docstring: infers a different number of prompt types than was originally called.
docstring_tokens: infers a different number of prompt types than was originally called .
code: def refit_types(self, n_types, random_state=None, name=None):
  		"""
  			infers a different number of prompt types than was originally called.
  
  			:param n_types: number of types to learn
  			:param random_state: random seed
  			:param name: the name of the new type model. defaults to n_types.
  			:return: None
  		"""
  		self.pipe.named_steps['pt_model'].refit_types(n_types, random_state, name)
code_tokens: def refit_types ( self , n_types , random_state = None , name = None ) : self . pipe . named_steps [ 'pt_model' ] . refit_types ( n_types , random_state , name )
short_docstring: infers a different number of prompt types than was originally called.
short_docstring_tokens: infers a different number of prompt types than was originally called .
comment: """
  			infers a different number of prompt types than was originally called.
  
  			:param n_types: number of types to learn
  			:param random_state: random seed
  			:param name: the name of the new type model. defaults to n_types.
  			:return: None
  		"""