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GRPO, a reinforcement learning method popularized by DeepSeek-R1 reasoning models, differs from traditional PPO by computing rewards in relation to a set of outputs, bypassing the need for a separate 'Critic' model that consumes substantial VRAM. This enables developers to train 'Reasoning AI' models—proficient in sequential logic and mathematical proofs—on local machines.
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