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Reinforcement learning training with DDPO

You can fine-tune Stable Diffusion on a reward function via reinforcement learning with the πŸ€— TRL library and πŸ€— Diffusers. This is done with the Denoising Diffusion Policy Optimization (DDPO) algorithm introduced by Black et al. in Training Diffusion Models with Reinforcement Learning, which is implemented in πŸ€— TRL with the [~trl.DDPOTrainer].

For more information, check out the [~trl.DDPOTrainer] API reference and the Finetune Stable Diffusion Models with DDPO via TRL blog post.