Create README.md

README.md

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+---
+base_model:
+- CompVis/stable-diffusion-v1-4
+pipeline_tag: text-to-image
+tags:
+- art
+- biology
+---
+<h1 align="center">**The Superposition of Diffusion Models Using the Itô Density Estimator**: Pipeline</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 v1-4](https://huggingface.co/CompVis/stable-diffusion-v1-4) based on theorems from the paper [The Superposition of Diffusion Models Using the Itô Density Estimator](https://www.arxiv.org/abs/2412.17762).
+
+<p align="center">
+<img src="https://huggingface.co/superdiff/pipeline/blob/main/superdiff_small.gif" alt="drawing" style="width:500px;">
+</p>
+
+
+## Example usage
+
+```
+from PIL import Image
+from diffusers import DiffusionPipeline
+
+image = pipeline("a flamingo", "a candy cane", seed=1, num_inference_steps=1000, batch_size=1)
+image = Image.fromarray(image.cpu().numpy())
+image.save("superdiff_output.png")
+```
+
+Arguments that can be set by user in `pipeline()`:
+
+- `prompt_1`: text prompt describing first concept to superimpose (e.g. "a flamingo")
+- `prompt_2`: text prompt describing second concept to superimpose (e.g. "a candy cane")
+- `seed`: seed for random noise generator for reproducibility; for non-deterministic outputs, do not provide value
+- `num_inference_steps`: number of denoising steps (we recommend 1000!)
+- `batch_size`: batch size
+- `lift`: bias value that favours generation towards one prompt over the other
+- `guidance_scale`: scale for classifier-free guidance
+- `height`, `width`: height and width of generated images
+
+To replicate images from Section 4.2 of the paper, you can use the following:
+
+```
+image = pipeline(prompt_1, prompt_2, seed=1, num_inference_steps=1000, batch_size=20, lift=0.0, guidance_scale=7.5)
+```
+
+## 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}
+}
+```