Microsoft and Hugging Face released the ThinkingBox‑Training code on GitHub. They used a reward derived from database‑state checks to fine‑tune the Qwen3.8‑27B model. After 50 GRPO steps, the model’s pass@1 rose from 51.70% to 60.78% and the number of tasks it got right on every of 20 attempts grew from 38 (7.5%) to 107 (21.1%). The improvement came with a modest drop in at‑least‑once coverage.
Why it matters
For companies that need reliable database updates, the fine‑tuned model is about three times more likely to get a task right every time.
