JIANG: Chinese Open Foundation Language Model

Qinhua Duan, Wenchao Gu, Yujia Chen, Wenxin Mao, Zewen Tian +1 more
8/1/2023
cs.CLcs.AI

No confident code implementation found for this paper.

Abstract

With the advancements in large language model technology, it has showcased capabilities that come close to those of human beings across various tasks. This achievement has garnered significant interest from companies and scientific research institutions, leading to substantial investments in the research and development of these models. While numerous large models have emerged during this period, the majority of them have been trained primarily on English data. Although they exhibit decent performance in other languages, such as Chinese, their potential remains limited due to factors like vocabulary design and training corpus. Consequently, their ability to fully express their capabilities in Chinese falls short. To address this issue, we introduce the model named JIANG (Chinese pinyin of ginger) specifically designed for the Chinese language. We have gathered a substantial amount of Chinese corpus to train the model and have also optimized its structure. The extensive experimental results demonstrate the excellent performance of our model.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Cite this paper

@article{duan2023jiang,
  title  = {JIANG: Chinese Open Foundation Language Model},
  author = {Qinhua Duan and Wenchao Gu and Yujia Chen and Wenxin Mao and Zewen Tian and Hui Cao},
  year   = {2023},
  eprint = {2308.00624},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2308.00624v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2308.00624.svg)](https://codeofpaper.com/paper/2308.00624)

Discussion