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remove outdated info, add entry for TAESD vae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
[[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
@@ -18,27 +22,13 @@ All examples are non-cherrypicked unless specified otherwise.
# 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)
![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
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.
# 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
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