Fine-Tuning LLMs: From Zero to Hero with Python & Ollama 🚀

Author(s): MahendraMedapati

Originally published on Towards AI.

Ever wondered how to make AI models actually useful for YOUR specific needs? Let me show you how I went from confused beginner to fine-tuning wizard in just one weekend!

Picture this: You’re trying to get ChatGPT to extract product information from messy HTML, but it keeps giving you different formats every time. Sometimes it’s a paragraph, sometimes bullet points, sometimes it just… forgets half the data. Sound familiar?

The article explores the process of fine-tuning language models, detailing the steps needed to make models like ChatGPT more efficient and tailored to specific tasks. It emphasizes the importance of selecting appropriate training data, setting up the necessary computational environment, and implementing techniques such as Low-Rank Adaptation (LoRA) for effective training. The author shares practical tips, common pitfalls to avoid, and insights into subsequent directions for further exploration in AI model fine-tuning.

Read the full blog for free on Medium.

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Published via Towards AI