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remove outdated info, add entry for TAESD vae

ClashSAN
2023-08-27 17:02:05 -04:00
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Features.md

@@ -4,7 +4,11 @@ All examples are non-cherrypicked unless specified otherwise.
# SD-XL # SD-XL
[[PR]](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/11757) | [[Stability-AI Github]](https://github.com/Stability-AI/generative-models) [[PR]](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/11757) | [[Stability-AI Github]](https://github.com/Stability-AI/generative-models)
Support for SD-XL was added in version `1.5.0`, with additional memory optimizations and built-in sequenced refiner inference added in version `1.6.0`.
Read here for a list of tips for optimizing inference: [Optimum-SDXL-Usage](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Optimum-SDXL-Usage)
## Downloads ## Downloads
@@ -18,27 +22,13 @@ All examples are non-cherrypicked unless specified otherwise.
# SD-XL BASE # SD-XL BASE
This is a model designed for generating quality `1024×1024`-sized images. It is **not** meant to generate good pictures at `512×512`. This is a model designed for generating quality `1024×1024`-sized images.
It's tested to produce same (or very close) images as Stability-AI's repo (need to set Random number generator source = CPU in settings) It's tested to produce same (or very close) images as Stability-AI's repo (need to set Random number generator source = CPU in settings)
![img](https://user-images.githubusercontent.com/20920490/253218112-c7c02951-0c1c-47f8-98a4-4fbdcb028712.png) ![img](https://user-images.githubusercontent.com/20920490/253218112-c7c02951-0c1c-47f8-98a4-4fbdcb028712.png)
```
- textual inversion should not work, embeddings need to be created specifically for SDXL.
- train tab will not work.
- DDIM, PLMS, UniPC samplers do not work for SDXL
```
```
- --lowvram, --medvram works
- attention optimizations work
- SDXL Loras work
- works at minimum 4gb gpu (30XX)
```
## SD-XL REFINER ## SD-XL REFINER
This secondary model is **designed** to process the `1024×1024` SD-XL image **near completion**, to further enhance and refine details in your final output picture. As of version 1.6.0, this is now implemented in the webui natively. This secondary model is **designed** to process the `1024×1024` SD-XL image **near completion**, to further enhance and refine details in your final output picture. As of version 1.6.0, this is now implemented in the webui natively.
@@ -612,6 +602,16 @@ unconditional denoising in the same batch.
This implementation of optimization does not require any modification to the original Stable Diffusion code. This implementation of optimization does not require any modification to the original Stable Diffusion code.
# TAESD
[Standard inference support added](https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/12311) in version `1.6.0`
With this lightweight VAE enabled via settings, it typically allows for very large, fast generations with a small quality loss.
This gain can be very large, maximum generations with --lowvram can increase from `1152x1152` to `2560x2560`
![image](https://github.com/AUTOMATIC1111/stable-diffusion-webui/assets/98228077/016fa4be-155d-433b-88b9-00cf7b452a8a)
# Face restoration # Face restoration
Lets you improve faces in pictures using either [GFPGAN](https://github.com/TencentARC/GFPGAN) or [CodeFormer](https://github.com/sczhou/CodeFormer). There is a checkbox in every tab to use face restoration, Lets you improve faces in pictures using either [GFPGAN](https://github.com/TencentARC/GFPGAN) or [CodeFormer](https://github.com/sczhou/CodeFormer). There is a checkbox in every tab to use face restoration,
and also a separate tab that just allows you to use face restoration on any picture, with a slider that controls how visible and also a separate tab that just allows you to use face restoration on any picture, with a slider that controls how visible