Stop Fine-Tuning Models You Don’t Need

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Stop Fine-Tuning Models You Don’t Need

Fine-tuning sounds like the answer until you factor in the cost, the data pipeline, and the six months before a bigger model makes yours obsolete. Most of the time, prompt engineering or better context gets you there. But sometimes it doesn't — and that's where things get interesting.

In this free night session, Aaron Gallant covers the real tradeoffs behind fine-tuning LLMs, from synthesizing training data with frontier models to running PEFT and QLoRA on constrained hardware. You'll learn when smaller, specialized models actually beat throwing money at a bigger one — and why data curation is the work nobody wants to talk about. Built for engineers who want to make the right call, not just the cool one.

Live and remote. Wednesday, June 3 at 5 PM CT. Register now.

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