readme: ---
  language: 
    - zh
  thumbnail: "url to a thumbnail used in social sharing"
  tags:
  - bart-base-chinese
  datasets:
  - lccc
  - kd_conv
  ---
  
  # dialogue-bart-base-chinese
  This is a seq2seq model fine-tuned on several Chinese dialogue datasets, from bart-base-chinese.
  
  
  # Spaces
  Now you can experience our model on HuggingFace Spaces [HIT-TMG/dialogue-bart-large-chinese](https://huggingface.co/spaces/HIT-TMG/dialogue-bart-large-chinese) .
  
  
  # Datasets
  We utilize 4 Chinese dialogue datasets from [LUGE](https://www.luge.ai/#/)
  
  |                              |            |                       |
  | ----                         | ----       | ----                  |
  |                              | Count      | Domain                |
  | Chinese Persona Chat (CPC)   | 23,000     | Open                  | 
  | LCCC                         | 11,987,759 | Open                  |
  | Emotional STC (ESTC)         | 899,207    | Open                  |
  | KdConv                       | 3,000      | Movie, Music, Travel  |
  |                              |            |                       |
  
  
  # Data format
  Input: `[CLS] 对话历史：<history> 知识：<knowledge> [SEP]`
  
  Output: `[CLS] <response> [SEP]`
  
  
  # Example
  ```python
  from transformers import BertTokenizer, BartForConditionalGeneration
  # Note that tokenizer is an object of BertTokenizer, instead of BartTokenizer
  tokenizer = BertTokenizer.from_pretrained("HIT-TMG/dialogue-bart-base-chinese")
  model = BartForConditionalGeneration.from_pretrained("HIT-TMG/dialogue-bart-base-chinese")
  # an example from CPC dev data
  history = ["可以 认识 一下 吗 ？", "当然 可以 啦 ， 你好 。", "嘿嘿 你好 ， 请问 你 最近 在 忙 什么 呢 ？", "我 最近 养 了 一只 狗狗 ， 我 在 训练 它 呢 。"]
  history_str = "对话历史：" + tokenizer.sep_token.join(history)
  input_ids = tokenizer(history_str, return_tensors='pt').input_ids
  output_ids = model.generate(input_ids)[0]
  print(tokenizer.decode(output_ids, skip_special_tokens=True))
   ```
   
   
   # Contact
   If you encounter any issue, feel free to contact us via the email: <u>yanshekwoo@foxmail.com</u>