Randeng MegatronT5 770M

🚀 Randeng-MegatronT5-770M

A Chinese T5-large model excelling in NLT tasks

🚀 Quick Start

Since there is no structure of Randeng-MegatronT5-770M in transformers library, you can find the structure of Randeng-MegatronT5-770M and run the codes in Fengshenbang-LM.

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

✨ Features

• Main Page: Fengshenbang
• Github: Fengshenbang-LM
• Good at solving NLT tasks, it serves as a Chinese T5-large model.

📦 Installation

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

💻 Usage Examples

Basic Usage

from fengshen import T5ForConditionalGeneration
from fengshen import T5Config
from fengshen import T5Tokenizer

tokenizer = T5Tokenizer.from_pretrained('IDEA-CCNL/Randeng-MegatronT5-770M')
config = T5Config.from_pretrained('IDEA-CCNL/Randeng-MegatronT5-770M')
model = T5ForConditionalGeneration.from_pretrained('IDEA-CCNL/Randeng-MegatronT5-770M')

📚 Documentation

Model Taxonomy

Model Information

To get a large-scale Chinese T5, we use of Megatron-LM and WuDao Corpora (180 GB version) for pre-training. Specifically, in the pre-training phase which cost about 14 days with 16 A100 GPUs.

📄 License

This project is licensed under the Apache-2.0 license.

📖 Citation

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}
}

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}},
}