--- license: apache-2.0 language: - en library_name: diffusers pipeline_tag: text-to-image --- # PhotoMaker Model Card
[**Project Page**](https://photo-maker.github.io/) **|** [**Paper (ArXiv)**](https://arxiv.org/abs/2312.04461) **|** [**Code**](https://github.com/TencentARC/PhotoMaker) [🤗 **Gradio demo (Realistic)**](https://huggingface.co/spaces/TencentARC/PhotoMaker) **|** [🤗 **Gradio demo (Stylization)**](https://huggingface.co/spaces/TencentARC/PhotoMaker-Style)
## Introduction Users can input one or several face photos, along with a text prompt, to receive a customized photo or painting within seconds (no training required!). Additionally, this model can be adapted to any base model based on SDXL or used in conjunction with other LoRA models. ### Realistic results ![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/6285a9133ab6642179158944/BYBZNyfmN4jBKBxxt4uxz.jpeg) ![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/6285a9133ab6642179158944/9KYqoDxfbNVLzVKZzSzwo.jpeg) ### Stylization results ![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/6285a9133ab6642179158944/du884lcjpqqjnJIxpATM2.jpeg) ![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/6285a9133ab6642179158944/-AC7Hr5YL4yW1zXGe_Izl.jpeg) More results can be found in our [project page](https://photo-maker.github.io/) ## Model Details ### Model Description - **Developed by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Model type:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] - **Finetuned from model [optional]:** [More Information Needed] ## Bias, Risks, and Limitations [More Information Needed] ## Citation [optional] **BibTeX:** ```bibtex @article{li2023photomaker, title={PhotoMaker: Customizing Realistic Human Photos via Stacked ID Embedding}, author={Li, Zhen and Cao, Mingdeng and Wang, Xintao and Qi, Zhongang and Cheng, Ming-Ming and Shan, Ying}, booktitle={arXiv preprint arxiv:2312.04461}, year={2023} } ```