Randeng-T5-784M

主页面：封神榜
代码库：Fengshenbang-LM

简介 Brief Introduction

擅长处理自然语言转换任务，是中文版的mT5-large模型。

Good at handling NLT tasks, Chinese mT5-large.

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	mT5	784M	中文-Chinese

模型信息 Model Information

我们基于mT5-large模型，训练了其中文版本。为加速训练过程，我们仅选用T5分词器（sentence piece）中与中英文对应的词表及嵌入向量，并在悟道语料库（180G版本）上采用语料库自适应预训练（Corpus-Adaptive Pre-Training, CAPT）技术进行持续预训练。预训练目标为跨度破坏（span corruption）。具体而言，预训练阶段使用了封神框架，在16张A100显卡上耗时约96小时。

Based on mT5-large, we implement its Chinese version. In order to accelerate training, we only retrain the vocabulary and embedding corresponding to Chinese and English in T5tokenizer (sentence piece), and Corpus-Adaptive Pre-Training (CAPT) on the WuDao Corpora (180 GB version). The pretraining objective is span corruption. Specifically, we use the fengshen framework in the pre-training phase which cost about 96 hours with 16 A100 GPUs.

使用 Usage

from transformers import T5ForConditionalGeneration, AutoTokenizer
import torch
tokenizer=AutoTokenizer.from_pretrained('IDEA-CCNL/Randeng-T5-784M', use_fast=false)
model=T5ForConditionalGeneration.from_pretrained('IDEA-CCNL/Randeng-T5-784M')

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：

如果您将本资源用于您的工作，请引用我们的论文：

@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：

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

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

mT5

784M

中文-Chinese

模型信息 Model Information

from transformers import T5ForConditionalGeneration, AutoTokenizer import torch tokenizer=AutoTokenizer.from_pretrained('IDEA-CCNL/Randeng-T5-784M', use_fast=false) model=T5ForConditionalGeneration.from_pretrained('IDEA-CCNL/Randeng-T5-784M')

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：

如果您将本资源用于您的工作，请引用我们的论文：

@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：

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