AI largescale language model enterpriselevel applicatio

本文探讨了如何在HR管理系统中部署和整合大型语言模型,以处理大量复杂数据并提供准确结果。文章介绍了预训练、训练和后训练技术,并通过Python示例展示了如何构建应用。主要挑战包括模型部署、训练和人类参与的反馈循环。核心概念涉及BERT、细调和分词等。

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1.背景介绍

Introduction

As Artificial Intelligence (AI) and machine learning technologies have been widely applied to various aspects of human work, the importance of building high-quality natural language understanding technology has become increasingly felt by organizations such as HR departments. Although there are many existing tools available for Natural Language Processing (NLP), they still face challenges when facing a massive amount of data with high complexity. To address this problem, we need to develop advanced models that can process massive amounts of textual data and provide accurate results at scale while also maintaining good user experience.

To achieve these goals, companies need an end-to-end solution that integrate

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