Group Relative Policy Optimization (GRPO) is a reinforcement learning method that fine-tunes large language models for math and reasoning tasks using deterministic reward functions, eliminating the need for labeled data. The process involves generating multiple candidate responses, assigning rewards based on deterministic
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95% Agents die before production. The remaining 5% do this.Build a Reasoning LLM using GRPOSort: