Distillation is the most common trick in the post-training toolbox: sample from a stronger model, SFT on its outputs.
But what do you do when there's no stronger model to learn from?
We hit this problem while building the SFT and RL subsets of 🧬 FineDNA. Here's what worked 🧵
