(self, file_data=True, prefix=None,
                      max_length=512,
                      top_k=50,
                      top_p=0.9,
                      temperature=0.3,
                      return_sequences=2)
:param file_data: using the data passed to the client instance or not (bool).
        :param prefix: a string that you want the generated text to begin with
        :param max_length: the length of desired text you want (int)
        :param top_k: number of most frequent words in the vocab to be used in tokenization (int).
        :param top_p: p value between 0 and 1 (float)
        :param temperature: temperature to make the next word probability distribution sharper (float).
        :param return_sequences: how many different text sequences you want returned
        :return: generated text
:param file_data: using the data passed to the client instance or not (bool).
        :param prefix: a string that you want the generated text to begin with
        :param max_length: the length of desired text you want (int)
        :param top_k: number of most frequent words in the vocab to be used in tokenization (int).
        :param top_p: p value between 0 and 1 (float)
        :param temperature: temperature to make the next word probability distribution sharper (float).
        :param return_sequences: how many different text sequences you want returned
        :return: generated text
: param file_data : using the data passed to the client instance or not ( bool ) . : param prefix : a string that you want the generated text to begin with : param max_length : the length of desired text you want ( int ) : param top_k : number of most frequent words in the vocab to be used in tokenization ( int ) . : param top_p : p value between 0 and 1 ( float ) : param temperature : temperature to make the next word probability distribution sharper ( float ) . : param return_sequences : how many different text sequences you want returned : return : generated text
def generate_text(self, file_data=True, prefix=None,
                      max_length=512,
                      top_k=50,
                      top_p=0.9,
                      temperature=0.3,
                      return_sequences=2):
        """
        :param file_data: using the data passed to the client instance or not (bool).
        :param prefix: a string that you want the generated text to begin with
        :param max_length: the length of desired text you want (int)
        :param top_k: number of most frequent words in the vocab to be used in tokenization (int).
        :param top_p: p value between 0 and 1 (float)
        :param temperature: temperature to make the next word probability distribution sharper (float).
        :param return_sequences: how many different text sequences you want returned
        :return: generated text
        """
        self.models['text_generation'] = generate_text(self=self,
                                                       file_data=file_data,
                                                       prefix=prefix,
                                                       max_length=max_length,
                                                       top_k=top_k,
                                                       top_p=top_p,
                                                       temperature=temperature,
                                                       return_sequences=return_sequences)

        self.latest_model = 'text_generation'
        clearLog()
def generate_text ( self , file_data = True , prefix = None , max_length = 512 , top_k = 50 , top_p = 0.9 , temperature = 0.3 , return_sequences = 2 ) : self . models [ 'text_generation' ] = generate_text ( self = self , file_data = file_data , prefix = prefix , max_length = max_length , top_k = top_k , top_p = top_p , temperature = temperature , return_sequences = return_sequences ) self . latest_model = 'text_generation' clearLog ( )