Choosing an LLM: The 2024 getting started guide to open source LLMs

In 2023, AI technology saw an unprecedented surge, with numerous new tools and features emerging, many of which rely on large language models (LLMs), particularly open-source variants. These LLMs, built on neural network architectures, are capable of performing a wide range of natural language processing tasks, making them instrumental in automating business functions across industries, from creating chatbots to enhancing cloud security. However, the effectiveness of LLMs is contingent on high-quality training data, and challenges such as data privacy and the risk of inaccurate outputs remain. Open-source LLMs, which are freely available and modifiable, offer significant flexibility for businesses without licensing costs, in contrast to proprietary models like OpenAI's GPT series. The guide reviews popular open-source LLMs, such as GPT-NeoX-20B, Llama 2, and BLOOM, highlighting their unique features, intended use cases, and complexity levels. It advises companies to assess considerations like cost, accuracy, performance, data security, and team expertise when selecting an LLM to ensure it aligns with their specific needs and capabilities.