| 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_forward = 'danyaljj/opengpt2_pytorch_forward' | |
| encoder = Encoder() | |
| model_backward = OpenGPT2LMHeadModel.from_pretrained(path_to_forward) | |
| input = "She tried to win but" | |
| input_ids = encoder.encode(input) | |
| input_ids = torch.tensor([input_ids ], dtype=torch.int) | |
| print(input_ids) | |
| output = model_backward.generate(input_ids) | |
| output_text = encoder.decode(output.tolist()[0]) | |
| print(output_text) | |
| ``` | |
| Download the additional files from here: https://github.com/peterwestuw/GPT2ForwardBackward | |