Community turns tiny Gemma models into reasoning engines on a single Kaggle TPU
The Google Tunix Hackathon showed community can turn lightweight Gemma models into general reasoning engines using a two‑stage post‑training pipeline—LoRA‑based supervised fine‑tuning followed by rubric‑driven reinforcement learning on a single Kaggle TPU v5e‑8. The recipe proves effective reasoning training is possible on modest compute, opening doors for broader adoption.