readme: This model provides a Chinese GPT-2 language model trained with SimCTG on the LCCC benchmark [(Wang et al., 2020)](https://arxiv.org/pdf/2008.03946v2.pdf) based on our paper [_A Contrastive Framework for Neural Text Generation_](https://arxiv.org/abs/2202.06417).
  
  We provide a detailed tutorial on how to apply SimCTG and Contrastive Search in our [project repo](https://github.com/yxuansu/SimCTG#4-huggingface-style-tutorials-back-to-top). In the following, we illustrate a brief tutorial on how to use our approach to perform text generation.
  
  ## 1. Installation of SimCTG:
  ```yaml
  pip install simctg --upgrade
  ```
  
  ## 2. Initialize SimCTG Model:
  ```python
  import torch
  # load SimCTG language model
  from simctg.simctggpt import SimCTGGPT
  model_name = r'cambridgeltl/simctg_lccc_dialogue'
  model = SimCTGGPT(model_name)
  model.eval()
  tokenizer = model.tokenizer
  eos_token = '[SEP]'
  eos_token_id = tokenizer.convert_tokens_to_ids([eos_token])[0]
  ```
  
  ## 3. Prepare the Text Prefix:
  ```python
  context_list = ['刺猬很可爱！以前别人送了只没养，味儿太大！', '是很可爱但是非常臭', '是啊，没办法养', '那个怎么养哦不会扎手吗']
  prefix_text = eos_token.join(context_list).strip(eos_token) + eos_token
  print ('Prefix is: {}'.format(prefix_text))
  tokens = tokenizer.tokenize(prefix_text)
  input_ids = tokenizer.convert_tokens_to_ids(tokens)
  input_ids = torch.LongTensor(input_ids).view(1,-1)
  ```
  
  ## 4. Generate Text with Contrastive Search:
  ```python
  beam_width, alpha, decoding_len = 5, 0.6, 64
  output = model.fast_contrastive_search(input_ids=input_ids, beam_width=beam_width, alpha=alpha, 
                                         decoding_len=decoding_len, end_of_sequence_token_id=eos_token_id,
                                         early_stop=True)  
                                             
  print("Output:\n" + 100 * '-')
  print(''.join(tokenizer.decode(output)))
  '''
    Prefix is: 刺猬很可爱！以前别人送了只没养，味儿太大！[SEP]是很可爱但是非常臭[SEP]是啊，没办法养[SEP]那个怎么养哦不会扎手吗[SEP]
    Output:
    ----------------------------------------------------------------------------------------------------
    刺猬很可爱！以前别人送了只没养，味儿太大！[SEP]是很可爱但是非常臭[SEP]是啊，没办法养[SEP]那个怎么养哦不会扎手吗[SEP]我觉得还好，就是有点臭
  '''
  ```
  
  For more details of our work, please refer to our main [project repo](https://github.com/yxuansu/SimCTG).
  
  ## 5. Citation:
  If you find our paper and resources useful, please kindly leave a star and cite our paper. Thanks!
  
  ```bibtex
  @article{su2022contrastive,
    title={A Contrastive Framework for Neural Text Generation},
    author={Su, Yixuan and Lan, Tian and Wang, Yan and Yogatama, Dani and Kong, Lingpeng and Collier, Nigel},
    journal={arXiv preprint arXiv:2202.06417},
    year={2022}
  }
  ```
  
  
  