Nebius Guide: Four Ways to Adapt Open-Weight Models — SFT, Preference Tuning, RL, Distillation
demian_ai · x · 2026-11-13
Nebius published a guide covering four ways to adapt open-weight models to your own data and workflows: supervised fine-tuning, preference tuning, RL, and distillation. It explains what feedback each method requires and how to test whether the adapted model meets quality, latency, and cost targets on real tasks, with examples from Revolut, Slingshot AI, and other Nebius customers — benefits include more accurate customer-record matching, more reliable tool use, and lower serving costs from smaller models.
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