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Fine-Tuning a Model on 100 Hand-Edited Answers

Fine-Tuning a Model on 100 Hand-Edited Answers

Episode 5393 Published 3 weeks, 5 days ago
Description
Most coverage of personal fine-tuning leads with the same line: tens of thousands of examples, a rack of GPUs, a research team. That story is mostly wrong. For a stylistic fine-tune — changing tone, personality, and response structure — the numbers are comically small by comparison. This episode walks through the full pipeline: how many hand-edited prompt-response pairs you actually need (somewhere between 100 and 1,000, with the first hundred doing most of the work), where the initial drafts come from, how long training takes on a frontier model with Unsloth, and where the resulting weights live once they're trained. Along the way: what separates a high-quality edit from a wasted slot, why model collapse makes the human step load-bearing, and whether the same pipeline could fine-tune a podcast's own script-generation path. Episode #109707 — open it directly at myweirdprompts.com/109707
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