SFT — Supervised Fine-Tuning
Definition: Training a base model on curated input-output pairs to specialize its behavior. SFT is where most domain models actually get their personality — long before RLHF cleans up the rough edges.
Example
SFT on 4,000 hand-written examples turned a generic model into one that wrote in our brand voice consistently.
When you'll hear it
SFT shows up most often in AI strategy reviews, model evaluation discussions, and product roadmap meetings. When someone uses it, they're usually referring to supervised fine-tuning — and they expect the room to already know what that means.
FAQs
What does SFT stand for?
SFT stands for Supervised Fine-Tuning.
What does SFT mean in AI and machine-learning?
Training a base model on curated input-output pairs to specialize its behavior. SFT is where most domain models actually get their personality — long before RLHF cleans up the rough edges.
Where will I hear SFT used at work?
SFT comes up most often in AI strategy reviews, model evaluation discussions, and product roadmap meetings. It's used as shorthand for supervised fine-tuning, so people assume you already know the term.
Related terms
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