Update README.md

README.md

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----
-license: apache-2.0
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+# GradSPO: A Gradient Guidance Perspective on Stepwise Preference Optimization for Diffusion Models
+
+
+This repository provides **public LoRA checkpoints trained with GradSPO** for **Stable Diffusion v1.5** and **SDXL**.
+
+**GradSPO** reframes **stepwise preference optimization (SPO)** as learning from **noisy reward signals**, explicitly reducing this noise through **gradient guidance**. This results in **stronger reward signals** and achieves **improved preference alignment**.
+
+All released checkpoints are **LoRA weights only** and must be loaded on top of their corresponding base models.
+
+The official training code is available at:  
+https://github.com/JoshuaTTJ/GradSPO
+
+---
+
+## Usage
+
+### SDXL (LoRA)
+
+```python
+from diffusers import StableDiffusionXLPipeline
+import torch
+
+pipe = StableDiffusionXLPipeline.from_pretrained(
+    "stabilityai/stable-diffusion-xl-base-1.0",
+    torch_dtype=torch.float16,
+)
+
+pipe.load_lora_weights("./sd1_5")
+
+pipe = pipe.to("cuda")
+
+prompt = "A cat holding a sign that says hello world"
+
+generator = torch.Generator(device="cuda").manual_seed(42)
+image = pipe(
+    prompt=prompt,
+    guidance_scale=5.0,
+    num_inference_steps=20,
+    generator=generator,
+    output_type="pil",
+).images[0]
+
+image.save("img_sdxl.png")
+```
+
+---
+
+### Stable Diffusion v1.5 (LoRA)
+
+```python
+from diffusers import StableDiffusionPipeline
+import torch
+
+pipe = StableDiffusionPipeline.from_pretrained(
+    "sd-legacy/stable-diffusion-v1-5",
+    torch_dtype=torch.float16,
+)
+
+pipe.load_lora_weights("./sdxl")
+
+pipe = pipe.to("cuda")
+
+prompt = "a photo of a cat"
+
+generator = torch.Generator(device="cuda").manual_seed(42)
+image = pipe(
+    prompt=prompt,
+    guidance_scale=5.0,
+    num_inference_steps=20,
+    generator=generator,
+    output_type="pil",
+).images[0]
+
+image.save("img_sd15.png")
+```
+
+---
+
+## Citation
+
+If you find GradSPO useful in your research, please consider citing our work:
+
+```bibtex
+@inproceedings{
+tee2025a,
+title={A Gradient Guidance Perspective on Stepwise Preference Optimization for Diffusion Models},
+author={Joshua Tian Jin Tee and Hee Suk Yoon and Abu Hanif Muhammad Syarubany and Eunseop Yoon and Chang D. Yoo},
+booktitle={The Thirty-ninth Annual Conference on Neural Information Processing Systems},
+year={2025},
+url={https://openreview.net/forum?id=d6lIOnvOX2}
+}
+```