Randeng-Transformer-1.1B-Denoise

Main Page:Fengshenbang
Github: Fengshenbang-LM

简介 Brief Introduction

基于Transformer-XL的中文句子改写。

Paraphrase Chinese sentences based on Transformer-XL.

模型分类 Model Taxonomy

需求 Demand	任务 Task	系列 Series	模型 Model	参数 Parameter	额外 Extra
通用 General	自然语言转换 NLT	燃灯 Randeng	Transformer	1.1B	中文-改写 Chinese-Paraphrase

模型信息 Model Information

在悟道语料库(280G版本)和标注的相似句子对数据集上进行预训练。

The Transformer-XL model was pre-trained on the Wudao Corpus (with 280G samples) and annotated similar-sentence pair dataset.

使用 Usage

加载模型 Loading Models

git clone https://github.com/IDEA-CCNL/Fengshenbang-LM.git

from fengshen.models.transfo_xl_paraphrase import TransfoXLModel
from transformers import T5Tokenizer as TransfoXLTokenizer


model = TransfoXLModel.from_pretrained('IDEA-CCNL/Randeng-TransformerXL-1.1B-Paraphrasing-Chinese')
tokenizer = TransfoXLTokenizer.from_pretrained('IDEA-CCNL/Randeng-TransformerXL-1.1B-Paraphrasing-Chinese',
                                               eos_token = '<|endoftext|>',                                    
                                               extra_ids=0)

使用示例 Usage Examples

from fengshen.models.transfo_xl_paraphrase import paraphrase_generatete
input_text = "年轻教师选择农村学校，还是县城学校？"                                                 
res = paraphrase_generate(model, tokenizer, input_text, device=0)                                             
print(res)
#

引用 Citation

如果您在您的工作中使用了我们的模型，可以引用我们的论文：

If you are using the resource for your work, please cite the our paper:

@article{fengshenbang,
  author    = {Jiaxing Zhang and Ruyi Gan and Junjie Wang and Yuxiang Zhang and Lin Zhang and Ping Yang and Xinyu Gao and Ziwei Wu and Xiaoqun Dong and Junqing He and Jianheng Zhuo and Qi Yang and Yongfeng Huang and Xiayu Li and Yanghan Wu and Junyu Lu and Xinyu Zhu and Weifeng Chen and Ting Han and Kunhao Pan and Rui Wang and Hao Wang and Xiaojun Wu and Zhongshen Zeng and Chongpei Chen},
  title     = {Fengshenbang 1.0: Being the Foundation of Chinese Cognitive Intelligence},
  journal   = {CoRR},
  volume    = {abs/2209.02970},
  year      = {2022}
}

也可以引用我们的网站:

You can also cite our website:

@misc{Fengshenbang-LM,
  title={Fengshenbang-LM},
  author={IDEA-CCNL},
  year={2021},
  howpublished={\url{https://github.com/IDEA-CCNL/Fengshenbang-LM}},
}