How to Customize NVIDIA Nemotron 3 Nano With RLVR in Prime Intellect Lab

Customize NVIDIA Nemotron 3 Nano with reinforcement learning with verifiable rewards (RLVR) using Prime Intellect Lab. This tutorial walks through a complete customization workflow: baseline Nemotron 3 Nano in the math-python environment, train a LoRA adapter with reinforcement learning with verifiable rewards, deploy it, and compare results. The goal is to solve tool-assisted math problems within five turns. After 100 training steps—about one hour and 45 minutes—the adapter completes more tasks with fewer tool calls. The experiment costs less than $5 and converts several incorrect baseline results to correct answers without losing previously correct responses. See how reward increases as turn count falls, then use the workflow as a starting point for your own model customization. #Tutorial #ReinforcementLearning #NVIDIANemotron