Don’t Fine-Tune Your LLMs

You’re building a solution with large-language models and want to optimize performance on your data. So you need to fine-tune the model, right? Probably not.

Welcome to Episode 35 of Prolego’s Generative AI Series. In this week’s episode I discuss what fine-tuning is, what it isn’t, and why you probably don’t want to do it.

🔍 What’s Inside This Episode?

• In this episode, we clarify the concept of fine-tuning in the context of LLM optimization and we explain why you should avoid rushing into fine-tuning.
• We also discuss the limitations of fine-tuning, its potential pitfalls, and recommend other optimization techniques that we outline in our LLM Optimization Playbook.