Create README.md

README.md

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+---
+base_model:
+- stabilityai/stable-diffusion-xl-base-1.0
+pipeline_tag: text-to-image
+tags:
+- art
+---
+<h1 align="center">The Superposition of Diffusion Models Using the Itô Density Estimator: <em>Pipeline</em></h1>
+
+ <p align="center">
+ <a href="https://arxiv.org/abs/2412.17762"><img src="https://img.shields.io/badge/Arxiv-2412.17762-red?style=for-the-badge&logo=Arxiv" alt="arXiv"/></a>
+</p>
+
+This pipeline shows how to superimpose different text prompts from [Stable Diffusion-XL 1.0](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0) based the paper [The Superposition of Diffusion Models Using the Itô Density Estimator](https://www.arxiv.org/abs/2412.17762). The authors would like to thank Viktor Ohanesian for developing the SD-XL pipeline.
+
+<p align="center">
+<img src="https://huggingface.co/superdiff/superdiff-sd-v1-4/resolve/main/superdiff_small.gif" alt="drawing" style="width:500px;">
+</p>
+
+## Requirements
+
+This pipeline can be run with the following packages & versions:
+- `PyTorch 2.5.1`
+- `Diffusers 0.32.1`
+- `Accelerate 1.2.1`
+- `Transformers 4.47.1`
+
+You can install these with:
+
+```
+pip install torch
+pip install diffusers accelerate transformers
+```
+
+## Example usage
+
+```
+from PIL import Image
+from diffusers import DiffusionPipeline
+
+pipeline = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", custom_pipeline="superdiff/superdiff-sdxl-v1-0")
+output = pipeline("a flamingo", "a candy cane", seed=1, num_inference_steps=200, batch_size=1)
+
+image = Image.fromarray(output[0].cpu().numpy())
+image.save("superdiff_output.png")
+```
+
+Arguments that can be set by user in `pipeline()`:
+
+- `prompt_1` [required]: text prompt describing first concept to superimpose (e.g. "a flamingo")
+- `prompt_2`[required]: text prompt describing second concept to superimpose (e.g. "a candy cane")
+- `seed`[optional: default=None]: seed for random noise generator for reproducibility; for non-deterministic outputs, set to `None`
+- `num_inference_steps`[optional: default=1000]: number of denoising steps (we recommend 1000!)
+- `batch_size` [optional: default=1]: batch size
+- `guidance_scale` [optional: default=7.5]: scale for classifier-free guidance
+- `height`, `width` [optional: default=512]: height and width of generated images
+
+
+## Citation
+
+**BibTeX:**
+
+```
+@article{skreta2024superposition,
+  title={The Superposition of Diffusion Models Using the It$\backslash$\^{} o Density Estimator},
+  author={Skreta, Marta and Atanackovic, Lazar and Bose, Avishek Joey and Tong, Alexander and Neklyudov, Kirill},
+  journal={arXiv preprint arXiv:2412.17762},
+  year={2024}
+}
+```