[[open-in-colab]]  
[Stable Diffusion XL](https://huggingface.co/papers/2307.01952) (SDXL) is a powerful text-to-image generation model that iterates on the previous Stable Diffusion models in three key ways:  
1. the UNet is 3x larger and SDXL combines a second text encoder (OpenCLIP ViT-bigG/14) with the original text encoder to significantly increase the number of parameters
2. introduces size and crop-conditioning to preserve training data from being discarded and gain more control over how a generated image should be cropped
3. introduces a two-stage model process; the *base* model (can also be run as a standalone model) generates an image as an input to the *refiner* model which adds additional high-quality details  
This guide will show you how to use SDXL for text-to-image, image-to-image, and inpainting.  
Before you begin, make sure you have the following libraries installed:  
```py
# uncomment to install the necessary libraries in Colab
#!pip install -q diffusers transformers accelerate invisible-watermark>=0.2.0
```  
<Tip warning={true}>  
We recommend installing the [invisible-watermark](https://pypi.org/project/invisible-watermark/) library to help identify images that are generated. If the invisible-watermark library is installed, it is used by default. To disable the watermarker:  
```py
pipeline = StableDiffusionXLPipeline.from_pretrained(..., add_watermarker=False)
```  
</Tip>
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/using-diffusers/sdxl.md