readme: West et al.'s model from their "reflective decoding" paper. 
  
  Sample usage: 
  
  ```python
  import torch
  from modeling_opengpt2 import OpenGPT2LMHeadModel
  from padded_encoder import Encoder
  
  path_to_backward = 'danyaljj/opengpt2_pytorch_backward'
  
  encoder = Encoder()
  model_backward = OpenGPT2LMHeadModel.from_pretrained(path_to_backward)
  
  input = "until she finally won."
  input_ids = encoder.encode(input)
  input_ids = torch.tensor([input_ids[::-1] ], dtype=torch.int)
  print(input_ids)
  
  output = model_backward.generate(input_ids)
  
  output_text = encoder.decode(output.tolist()[0][::-1])
  
  print(output_text)
  ```
  
  Download the additional files from here: https://github.com/peterwestuw/GPT2ForwardBackward
  
  