In the evolving landscape of 5G networks, Network Data Analytics Function (NWDAF) emerges as a key component, interacting with core network elements to enhance data collection, model training, and analytical outcomes. Language Models (LLMs), with their state-of-the-art capabilities in natural language processing, have been successful in numerous fields. In particular, LLMs enhanced through instruction fine-tuning have demonstrated their effectiveness by employing sets of instructions to precisely tailor the model’s responses and behavior. However, it requires collecting a large pool of high-quality training data regarding the precise domain knowledge and the corresponding programming codes. In this paper, we present an open-source mobile network-specialized LLM, Mobile-LLaMA, which is an instruction-fine-tuned variant of the LLaMA 2 13B model. We build Mobile-LLaMA by instruction fine-tuning LLaMA 2 13B with our own network analysis data collected from publicly available, real-world 5G network datasets, and expanded its capabilities through a self-instruct framework utilizing OpenAI’s pre-trained models (PMs). Mobile-LLaMA has three main functions: packet analysis, IP routing analysis, and performance analysis, enabling it to provide network analysis and contribute to the automation and artificial intelligence (AI) required for 5G network management and data analysis. Our evaluation demonstrates Mobile-LLaMA’s proficiency in network analysis code generation, achieving a score of 247 out of 300, surpassing GPT-3.5’s score of 209.

中文翻译：

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Mobile-LLaMA：用于 5G 网络分析的指令微调开源LLM


在不断发展的 5G 网络格局中，网络数据分析功能 (NWDAF) 成为关键组件，与核心网络元素交互以增强数据收集、模型训练和分析结果。语言模型（ LLMs ）凭借其在自然语言处理方面最先进的能力，在许多领域取得了成功。特别是，通过指令微调增强的LLMs已经通过使用指令集来精确定制模型的响应和行为来证明其有效性。然而，它需要收集大量关于精确领域知识和相应编程代码的高质量训练数据。在本文中，我们提出了一种开源移动网络专用LLM ，Mobile-LLaMA，它是 LLaMA 2 13B 模型的指令微调变体。我们使用从公开的真实 5G 网络数据集中收集的我们自己的网络分析数据，通过指令微调 LLaMA 2 13B 来构建 Mobile-LLaMA，并通过利用 OpenAI 预训练模型 (PM) 的自指导框架扩展其功能。 Mobile-LLaMA具有三大功能：数据包分析、IP路由分析和性能分析，使其能够提供网络分析，并为5G网络管理和数据分析所需的自动化和人工智能（AI）做出贡献。我们的评估表明 Mobile-LLaMA 在网络分析代码生成方面的熟练程度，在满分 300 分中获得 247 分，超过了 GPT-3.5 的 209 分。