mapo-t2i
/

mapo-pick-style-pixel-art

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 ---
 library_name: diffusers
 ---
-# Model Card for Model ID
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-This is the model card of a 🧨 diffusers model that has been pushed on the Hub. This model card has been automatically generated.
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 ---
+license: openrail++
 library_name: diffusers
+tags:
+- text-to-image
+- text-to-image
+- diffusers-training
+- diffusers
+- stable-diffusion-xl
+- stable-diffusion-xl-diffusers
+base_model: stabilityai/stable-diffusion-xl-base-1.0
 ---
+# Margin-aware Preference Optimization for Aligning Diffusion Models without Reference
+<div align="center">
+<img src="assets/mapo_overview.png" width=750/>
+</div><br>
+We propose **MaPO**, a reference-free, sample-efficient, memory-friendly alignment technique for text-to-image diffusion models. For more details on the technique, please refer to our paper [here] (TODO).
+## Developed by
+* Jiwoo Hong<sup>*</sup> (KAIST AI)
+* Sayak Paul<sup>*</sup> (Hugging Face)
+* Noah Lee (KAIST AI)
+* Kashif Rasul (Hugging Face)
+* James Thorne (KAIST AI)
+* Jongheon Jeong (Korea University)
+## Dataset
+This model was fine-tuned from [Stable Diffusion XL](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0) on the [pixel art split of Pick-Style](https://huggingface.co/datasets/mapo-t2i/pick-style-pixel-art).
+## Training Code
+Refer to our code repository [here](https://github.com/mapo-t2i/mapo).
+## Inference
+```python
+from diffusers import DiffusionPipeline, AutoencoderKL, UNet2DConditionModel
+import torch
+sdxl_id = "stabilityai/stable-diffusion-xl-base-1.0"
+vae_id = "madebyollin/sdxl-vae-fp16-fix"
+unet_id = "mapo-t2i/mapo-pick-style-pixel-art"
+vae = AutoencoderKL.from_pretrained(vae_id, torch_dtype=torch.float16)
+unet = UNet2DConditionModel.from_pretrained(unet_id, subfolder='unet', torch_dtype=torch.float16)
+pipeline = DiffusionPipeline.from_pretrained(sdxl_id, vae=vae, unet=unet, torch_dtype=torch.float16).to("cuda")
+prompt = "portrait of gorgeous cyborg with golden hair, high resolution"
+image = pipeline(prompt=prompt, num_inference_steps=30).images[0]
+```
+For qualitative results, please visit our [project website] (TODO).
+## Citation
+```bibtex
+@misc{todo,
+    title={Margin-aware Preference Optimization for Aligning Diffusion Models without Reference},
+    author={Jiwoo Hong and Sayak Paul and Noah Lee and Kashif Rasuland James Thorne and Jongheon Jeong},
+    year={2024},
+    eprint={todo},
+    archivePrefix={arXiv},
+    primaryClass={cs.CV,cs.LG}
+}
+```