PrismaCoder-3B is a Qwen2.5-Coder-3B-Instruct fine-tune specialized for generating and editing Prisma ORM schemas and client code from natural-language instructions. It was trained with a full SFT → DPO → GRPO pipeline, using a verifier (gate) as both the data-quality filter and the reinforcement-learning reward signal. stage, LoRA weights merged into the base model between stages iterative self-play RL round (attempted; see Limitations) weights for release All stages used seed 20260830 and ran on a single Kaggle T4 GPU (16GB) with gradient checkpointing and paged 8-bit AdamW. verifier (LightValidator, "V0" in the project's internal gate numbering): it checks that generated Prisma…