add: entry for DDPO support. (#5250)

* add: entry for DDPO support.

* move to training

* address steven's comments./

docs/source/en/_toctree.yml

@@ -106,6 +106,8 @@
       title: Custom Diffusion
     - local: training/t2i_adapters
       title: T2I-Adapters
+    - local: training/ddpo
+      title: Reinforcement learning training with DDPO
     title: Training
   - sections:
     - local: using-diffusers/other-modalities

docs/source/en/training/ddpo.md

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+
+# Reinforcement learning training with DDPO
+
+You can fine-tune Stable Diffusion on a reward function via reinforcement learning with the 🤗 TRL library and 🤗 Diffusers. This is done with the Denoising Diffusion Policy Optimization (DDPO) algorithm introduced by Black et al. in [Training Diffusion Models with Reinforcement Learning](https://arxiv.org/abs/2305.13301), which is implemented in 🤗 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](https://huggingface.co/blog/trl-ddpo) blog post.
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