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A developer's guide to open source LLMs and generative AI - The GitHub Blog

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We all know that AI is changing the world. But what happens when you combine AI with the power of open source? Over the past year, there has been an explosion of open source generative AI projects on GitHub: by our count, more than 8,000. They range from commercially backed large language models (LLMs) like Meta’s LLaMA to experimental open source applications. These projects offer many benefits to open source developers and the machine learning community—and are a great way to start building new AI-powered features and applications. In this article, we’ll explore: Let’s jump in. By now, most of us are familiar with LLMs: neural network-based language models trained on vast quantities of data to mimic human behavior by performing various downstream tasks, like question answering, translation, and summarization. LLMs have disrupted the world with the introduction of tools like ChatGPT and GitHub Copilot. Open source LLMs differ from their closed counterparts regarding the source code (a

Gwen Davis is a senior content strategist at GitHub, where she writes about developer experience, AI-powered workflows, and career growth in tech.

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