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README.md

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----
-license: mit
----
+---
+license: mit
+base_model:
+- stabilityai/sdxl-turbo
+---
+
+# sdxl-turbo-unified-reward-dpo
+
+## Model Summary
+
+This model is trained on sdxl-turbo based on DPO preference data constructed by our [UnifiedReward-7B](https://huggingface.co/CodeGoat24/UnifiedReward-7b) for enhanced image generation quality.
+
+For further details, please refer to the following resources:
+- 📰 Paper: 
+- 🪐 Project Page: https://codegoat24.github.io/UnifiedReward/
+- 🤗 Model Collections: https://huggingface.co/collections/CodeGoat24/unifiedreward-models-67c3008148c3a380d15ac63a
+- 🤗 Dataset Collections: https://huggingface.co/collections/CodeGoat24/unifiedreward-training-data-67c300d4fd5eff00fa7f1ede
+- 👋 Point of Contact: [Yibin Wang](https://codegoat24.github.io)
+
+
+### Quick Start
+
+SDXL-Turbo does not make use of `guidance_scale` or `negative_prompt`, we disable it with `guidance_scale=0.0`.
+Preferably, the model generates images of size 512x512 but higher image sizes work as well.
+A **single step** is enough to generate high quality images.
+
+```py
+from diffusers import AutoPipelineForText2Image
+import torch
+
+pipe = AutoPipelineForText2Image.from_pretrained("CodeGoat24/sdxl-turbo-unified-reward-dpo", torch_dtype=torch.float16, variant="fp16")
+pipe.to("cuda")
+
+prompt = "A cinematic shot of a baby racoon wearing an intricate italian priest robe."
+
+image = pipe(prompt=prompt, num_inference_steps=1, guidance_scale=0.0).images[0]
+```
+
+## Citation
+
+```
+
+```