readme: ---
  language:
  - en
  tags:
  - pytorch
  - coai
  pipeline_tag: conversational
  
  ---
  
  [blenderbot-400M-distill](https://huggingface.co/facebook/blenderbot-400M-distill) fine-tuned on the [ESConv dataset](https://github.com/thu-coai/Emotional-Support-Conversation). Usage example:
  
  ```python
  import torch
  from transformers import AutoTokenizer
  from transformers.models.blenderbot import BlenderbotTokenizer, BlenderbotForConditionalGeneration
  
  def _norm(x):
      return ' '.join(x.strip().split())
  
  tokenizer = BlenderbotTokenizer.from_pretrained('thu-coai/blenderbot-400M-esconv')
  model = BlenderbotForConditionalGeneration.from_pretrained('thu-coai/blenderbot-400M-esconv')
  model.eval()
  
  utterances = [
      "I am having a lot of anxiety about quitting my current job. It is too stressful but pays well",
      "What makes your job stressful for you?",
      "I have to deal with many people in hard financial situations and it is upsetting",
      "Do you help your clients to make it to a better financial situation?",
      "I do, but often they are not going to get back to what they want. Many people are going to lose their home when safeguards are lifted",
  ]
  input_sequence = '  '.join([' ' + e for e in utterances]) + tokenizer.eos_token # add space prefix and separate utterances with two spaces
  input_ids = tokenizer.convert_tokens_to_ids(tokenizer.tokenize(input_sequence))[-128:]
  input_ids = torch.LongTensor([input_ids])
  
  model_output = model.generate(input_ids, num_beams=1, do_sample=True, top_p=0.9, num_return_sequences=5, return_dict=False)
  generation = tokenizer.batch_decode(model_output, skip_special_tokens=True)
  generation = [_norm(e) for e in generation]
  print(generation)
  
  utterances.append(generation[0]) # for future loop
  ```
  
  
  Please kindly cite the [original paper](https://aclanthology.org/2021.acl-long.269/) if you use this model:
  
  ```bib
  @inproceedings{liu-etal-2021-towards,
    title={Towards Emotional Support Dialog Systems},
    author={Liu, Siyang  and 
      Zheng, Chujie  and 
      Demasi, Orianna  and 
      Sabour, Sahand  and 
      Li, Yu  and 
      Yu, Zhou  and 
      Jiang, Yong  and 
      Huang, Minlie},
    booktitle={Proceedings of the 59th annual meeting of the Association for Computational Linguistics},
    year={2021}
  }
  ```
  