Update README.md

README.md

@@ -1,44 +0,0 @@
----
-tags:
-- text2text-generation
-- Chinese
-- seq2seq
-language: zh
----
-
-# Chinese BART-Base
-
-## Model description
-
-This is an implementation of Chinese BART-Base.
-
-[**CPT: A Pre-Trained Unbalanced Transformer for Both Chinese Language Understanding and Generation**](https://arxiv.org/pdf/2109.05729.pdf)
-
-Yunfan Shao, Zhichao Geng, Yitao Liu, Junqi Dai, Fei Yang, Li Zhe, Hujun Bao, Xipeng Qiu
-
-**Github Link:** https://github.com/fastnlp/CPT
-
-
-## Usage
-
-```python
->>> from transformers import BertTokenizer, BartForConditionalGeneration, Text2TextGenerationPipeline
->>> tokenizer = BertTokenizer.from_pretrained("fnlp/bart-base-chinese")
->>> model = BartForConditionalGeneration.from_pretrained("fnlp/bart-base-chinese")
->>> text2text_generator = Text2TextGenerationPipeline(model, tokenizer)  
->>> text2text_generator("北京是[MASK]的首都", max_length=50, do_sample=False)
-    [{'generated_text': '北 京 是 中 国 的 首 都'}]
-```
-
-**Note: Please use BertTokenizer for the model vocabulary. DO NOT use original BartTokenizer.**
-
-## Citation
-
-```bibtex
-@article{shao2021cpt,
-  title={CPT: A Pre-Trained Unbalanced Transformer for Both Chinese Language Understanding and Generation}, 
-  author={Yunfan Shao and Zhichao Geng and Yitao Liu and Junqi Dai and Fei Yang and Li Zhe and Hujun Bao and Xipeng Qiu},
-  journal={arXiv preprint arXiv:2109.05729},
-  year={2021}
-}
-```