The foundation, current situation and future prospects of pre-training large language models

Haoran Han, Siyao Wu, Jinyao Yang, Yizhuo Zhao
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Abstract

The field of artificial intelligence has developed rapidly recently, and large language model technology, as a representative technology of it, can provide general knowledge and make many downstream tasks easier and more convenient. However, although many people use large language models to do some work, they still lack a systematically summarized literature. Therefore, in this article, we made a systematic summary. We first wrote about the early large language models, then we presented the development of GPT and how to use the GPT model, then we introduced the advanced GPT models, and finally we mentioned the risks and challenges faced by the GPT model. Our work can help users better use large language models.
预训练大型语言模型的基础、现状和前景
人工智能领域近来发展迅速,大语言模型技术作为其中的代表性技术,可以提供常识性的知识,使许多下游任务变得更加简单方便。然而,虽然很多人利用大语言模型做了一些工作,但仍然缺乏系统总结的文献。因此,在本文中,我们做了系统的总结。我们首先写了早期的大型语言模型,然后介绍了 GPT 的发展以及如何使用 GPT 模型,接着介绍了先进的 GPT 模型,最后提到了 GPT 模型面临的风险和挑战。我们的工作可以帮助用户更好地使用大型语言模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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