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.

翻译：随着大语言模型技术的进步，其在各类任务中展现出接近人类的能力。这一成就引起了企业和科研机构的广泛关注，导致对这些模型的研究与开发投入了大量资源。尽管在此期间涌现出众多大模型，但大多数主要基于英文数据进行训练。虽然这些模型在中文等其他语言上表现出不错的性能，但由于词汇设计和训练语料等因素，其潜力仍受到限制。因此，它们在中文本地化表达能力上存在不足。为解决这一问题，我们提出了专门针对中文设计的模型“江”（Ginger的中文拼音）。我们收集了大量中文语料用于模型训练，并对其结构进行了优化。广泛的实验结果表明，我们的模型具有卓越的性能。