Open-Source LLMs: Introduction
Open-source large language models have evolved from early source-available releases (BLOOM, Llama) into a mature ecosystem of permissively licensed, highly capable models (Mistral, Qwen,...
Generative AI is one of the most impactful technologies to have emerged in the last decade. Many companies are racing to provide the best large language models (LLMs), both to capture market share and to solve real-world problems. Like every emergent field, there are many competing players.
On one side are large software companies that develop closed-source models and sell products built on top of them — OpenAI with ChatGPT, or Anthropic with Claude. On the other side are tech companies, research institutions, and collaborative communities that deliver open-source large language models. Like any open-source community, this ecosystem thrives on contributions from developers and researchers worldwide, fostering innovation and accessibility.
The main advantage of open-source models is that you can host them locally — on your own computer or on your organization's infrastructure. This means more privacy and more control over the model's capabilities.
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What's inside
5 sections- 1 Table of Contents
- 2 Module 1: Understanding Open-source LLMs
- 3 Module 2: Customizing and Deploying Open-source LLMs
- 4 Module 3: Surveying Leading Open-source LLMs and Their Use Cases
- 5 Summary
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