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Finally, the GPT-3 is trained with proximal policy optimization (PPO) applying benefits on the generated info through the reward model. LLaMA two-Chat [21] increases alignment by dividing reward modeling into helpfulness and safety rewards and making use of rejection sampling Together with PPO. The First 4 versions of LLaMA two-Chat are great-tune