code: def get_model(self, opt_fn, emb_sz, n_hid, n_layers, **kwargs):
          
          m = get_language_model(self.nt, emb_sz, n_hid, n_layers, self.pad_idx, **kwargs)
          model = SingleModel(to_gpu(m))
          return RNN_Learner(self, model, opt_fn=opt_fn)
docs: Method returns a RNN_Learner object, that wraps an instance of the RNN_Encoder module.
  
          Args:
              opt_fn (Optimizer): the torch optimizer function to use
              emb_sz (int): embedding size
              n_hid (int): number of hidden inputs
              n_layers (int): number of hidden layers
              kwargs: other arguments
  
          Returns:
              An instance of the RNN_Learner class.