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[CVPR 2024] X-Adapter: Adding Universal Compatibility of Plugins for Upgraded Diffusion Model
| Date | Stars |
|---|---|
| 2026-07-31 | 770 |
| 2026-08-06 | 770 |
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# X-Adapter
This repository is the official implementation of [X-Adapter](https://arxiv.org/abs/2312.02238).
**[X-Adapter: Adding Universal Compatibility of Plugins for Upgraded Diffusion Model](https://arxiv.org/abs/2312.02238)**
<br/>
[Lingmin Ran](),
[Xiaodong Cun](https://vinthony.github.io/academic/),
[Jia-Wei Liu](https://jia-wei-liu.github.io/),
[Rui Zhao](https://ruizhaocv.github.io/),
[Song Zijie](),
[Xintao Wang](https://xinntao.github.io/),
[Jussi Keppo](https://www.jussikeppo.com/),
[Mike Zheng Shou](https://sites.google.com/view/showlab)
<br/>
[](https://showlab.github.io/X-Adapter/)
[](https://arxiv.org/abs/2312.02238)
<em> X-Adapter enables plugins pretrained on the old version (e.g. SD1.5) directly work with the upgraded Model (e.g., SDXL) without further retraining.</em>
[//]: # (<p align="center">)
[//]: # (<img src="https://tuneavideo.github.io/assets/teaser.gif" width="1080px"/> )
[//]: # (<br>)
[//]: # (<em>Given a video-text pair as input, our method, Tune-A-Video, fine-tunes a pre-trained text-to-image diffusion model for text-to-video generation.</em>)
[//]: # (</p>)
### Thank @[kijai](https://github.com/kijai) for CumfyUI implementation [here](https://github.com/kijai/ComfyUI-Diffusers-X-Adapter)! Please refer to this [tutorial](https://www.reddit.com/r/StableDiffusion/comments/1asuyiw/xadapter/) for hyperparameter setting.
## News
- [17/02/2024] Inference code released
## Setup
### Requirements
```shell
conda create -n xadapter python=3.10
conda activate xadapter
pip install torch==1.13.1+cu116 torchvision==0.14.1+cu116 --extra-index-url https://download.pytorch.org/whl/cu116
pip install -r requirements.txt
```
Installing [xformers](https://github.com/facebookresearch/xformers) is highly recommended for high efficiency and low GPU cost.
### Weights
**[Stable Diffusion]** [Stable Diffusion](https://arxiv.org/abs/2112.10752) is a latent text-to-image diffusion model capable of generating photo-realistic images given any text input. The pre-trained Stable Diffusion models can be downloaded from Hugging Face (e.g., [Stable Diffusion v1-5](https://huggingface.co/runwayml/stable-diffusion-v1-5)). You can also use fine-tuned Stable Diffusion models trained on different styles (e.g., [Anything V4.0](https://huggingface.co/andite/anything-v4.0), [Redshift](https://huggingface.co/nitrosocke/redshift-diffusion), etc.).
**[ControlNet]** [Controlnet](https://github.com/lllyasviel/ControlNet) is a method to control diffusion models with spatial conditions. You can download the ControlNet family [here](https://huggingface.co/lllyasviel/ControlNet).
**[LoRA]** [LoRA](https://arxiv.org/abs/2106.09685) is a lightweight adapter to fine-tune large-scale pretrained model. It is widely used for style or identity customization in diffusion models. You can download LoRA from the diffusion community (e.g., [civitai](https://civitai.com/)).
### Checkpoint
Models can be downloaded from our [Hugging Face page](https://huggingface.co/Lingmin-Ran/X-Adapter). Put the checkpoint in folder `./checkpoint/X-Adapter`.
## Usage
After preparing all checkpoints, we can run inference code using different plugins. You can refer to this [tutorial](https://www.reddit.com/r/StableDiffusion/comments/1asuyiw/xadapter/) to quickly get started with X-Adapter.
### Controlnet Inference
Set `--controlnet_canny_path` or `--controlnet_depth_path` to ControlNet's path in the bash script. The default value is its Hugging Face model card.
sh ./bash_scripts/canny_controlnet_inference.sh
sh ./bash_scripts/depth_controlnet_inference.sh
### LoRA Inference
Set `--lora_model_path` to LoRA's checkpoint in the bash script. In this example we use [MoXin](https://civitai.com/modelsExcerpt of 4,751 characters
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