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---
license: apache-2.0
language:
- en
library_name: diffusers
pipeline_tag: text-to-image
datasets:
- litagin/moe-speech
---
# PhotoMaker Model Card
<div align="center">
[**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)
</div>
## Introduction
<!-- Provide a quick summary of what the model is/does. -->
Users can input one or a few 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 modules.
### Realistic results
### Stylization results
More results can be found in our [project page](https://photo-maker.github.io/)
## Model Details
It mainly contains two parts corresponding to two keys in loaded state dict:
1. `id_encoder` includes finetuned OpenCLIP-ViT-H-14 and a few fuse layers.
2. `lora_weights` applies to all attention layers in the UNet, and the rank is set to 64.
## Usage
You can directly download the model in this repository.
You also can download the model in python script:
```python
from huggingface_hub import hf_hub_download
photomaker_ckpt = hf_hub_download(repo_id="TencentARC/PhotoMaker", filename="photomaker-v1.bin", repo_type="model")
```
Then, please follow the instructions in our [GitHub repository](https://github.com/TencentARC/PhotoMaker).
## Limitations
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
- The model's customization performance degrades on Asian male faces.
- The model still struggles with accurately rendering human hands.
## Bias
While the capabilities of image generation models are impressive, they can also reinforce or exacerbate social biases.
## Citation
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
**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}
}
``` |