After the initial paper release, we have improved numerous things in the architecture, training and sampling, making Würstchen competitive to current state-of-the-art models in many ways. We are excited to release this new version together with Diffusers. Here is a list of the improvements.  
- Higher resolution (1024x1024 up to 2048x2048)
- Faster inference
- Multi Aspect Resolution Sampling
- Better quality  
We are releasing 3 checkpoints for the text-conditional image generation model (Stage C). Those are:  
- v2-base
- v2-aesthetic
- **(default)** v2-interpolated (50% interpolation between v2-base and v2-aesthetic)  
We recommend using v2-interpolated, as it has a nice touch of both photorealism and aesthetics. Use v2-base for finetunings as it does not have a style bias and use v2-aesthetic for very artistic generations.
A comparison can be seen here:  
<img src="https://github.com/dome272/Wuerstchen/assets/61938694/2914830f-cbd3-461c-be64-d50734f4b49d" width=500>
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/pipelines/wuerstchen.md