Deploying LLMs: Top Learning & Educational Resources to Get Started

Learn How to Put Your LLMs into Production

Deploying Large Language Models (LLMs) is pivotal in leveraging their capabilities across various applications, from enhancing user experiences to addressing privacy concerns. There are four distinct deployment techniques: local, demo, server, and edge deployment. 

In this article, you will be provided with a selection of learning resources for each deployment technique, equipping readers with the knowledge needed to navigate and implement these techniques effectively.

The article begins by emphasizing the significance of local deployment, offering insights into five free tools for running LLMs locally on personal devices. It then delves into demo deployment, where readers can learn to build interactive applications with minimal coding experience. Server deployment is subsequently addressed, guiding readers through the process of deploying LLMs using cloud platforms and containers. Finally, the article elucidates edge deployment, highlighting the benefits of embedding LLMs directly into real-world systems and providing resources for implementing this approach.

This comprehensive resource is tailored for individuals seeking to harness the power of LLMs across diverse deployment scenarios. Whether you are a novice exploring local deployment or an experienced developer venturing into edge computing, this article offers invaluable learning materials to accelerate your journey. Designed to empower AI enthusiasts, developers, and researchers alike, this article serves as a roadmap for deploying LLMs effectively and efficiently.