code: def from_text_files(cls, path, field, train, validation, test=None, bs=64, bptt=70, **kwargs):
          
          trn_ds, val_ds, test_ds = ConcatTextDataset.splits(
              path, text_field=field, train=train, validation=validation, test=test)
          return cls(path, field, trn_ds, val_ds, test_ds, bs, bptt, **kwargs)
docs: Method used to instantiate a LanguageModelData object that can be used for a
              supported nlp task.
  
          Args:
              path (str): the absolute path in which temporary model data will be saved
              field (Field): torchtext field
              train (str): file location of the training data
              validation (str): file location of the validation data
              test (str): file location of the testing data
              bs (int): batch size to use
              bptt (int): back propagation through time hyper-parameter
              kwargs: other arguments
  
          Returns:
              a LanguageModelData instance, which most importantly, provides us the datasets for training,
                  validation, and testing
  
          Note:
              The train, validation, and test path can be pointed to any file (or folder) that contains a valid
                  text corpus.