Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
stable diffusion webui with contrastive prompt tuning
| Date | Stars |
|---|---|
| 2026-08-01 | 866 |
| 2026-08-06 | 866 |
| 2026-08-12 | 865 |
| 2026-08-30 | 863 |
| 2026-09-04 | 862 |
| 2026-09-07 | 861 |
| 2026-09-30 | 862 |
| 2026-10-11 | 862 |
| 2026-11-04 | 862 |
Today
— stars today
This week
— stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.00%/day
# DreamArtist
Paper: [](https://arxiv.org/abs/2211.11337)
This repo is the official PyTorch implementation of ***"DreamArtist: Towards Controllable One-Shot Text-to-Image Generation via Contrastive Prompt-Tuning"***
with [Stable-Diffusion-webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui).
***Stable-Diffusion-webui Extension Version :*** [DreamArtist-sd-webui-extension](https://github.com/7eu7d7/DreamArtist-sd-webui-extension)
Everyone is an artist. Rome wasn't built in a day, but your artist dreams can be!
With just ***one*** training image DreamArtist learns the content and style in it, generating diverse high-quality images with high controllability.
Embeddings of DreamArtist can be easily combined with additional descriptions, as well as two learned embeddings.
# Setup and Running
Clone this repo.
```bash
git clone https://github.com/7eu7d7/DreamArtist-stable-diffusion
```
Following the [instructions of webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui#automatic-installation-on-windows) to install.
## Training and Usage
First create the positive and negative embeddings in ```DreamArtist Create Embedding``` Tab.
### Preview Setting
After that, the ```names``` of the positive and negative embedding (```{name}``` and ```{name}-neg```) should be filled into the
```txt2img Tab``` with some common descriptions. This will ensure a correct preview image.
### Train
Then, select positive embedding and set the parameters and image folder path in the ```Train``` Tab to start training.
The corresponding negative embedding is loaded automatically.
If your VRAM is low or you want save time, you can uncheck the ```reconstruction```.
[Recommended parameters](https://github.com/7eu7d7/DreamArtist-sd-webui-extension#pre-trained-embeddings)
***better to train without filewords***
Remember to check the option below, otherwise the preview is wrong.
### Inference
Fill the trained positive and negative embedding into txt2img to generate with DreamArtist prompt.
## Tested models (need ema version):
+ Stable Diffusion v1.5
+ animefull-latest
+ Anything v3.0
Embeddings can be transferred between different models of the same dataset.
## Pre-trained embeddings:
[Download](https://github.com/7eu7d7/DreamArtist-stable-diffusion/releases/tag/embeddings_v2)
| Name | Model | Image | embedding length <br> (Positive, Negative) | iter | lr | cfg scale |
|------------|------------------|--------------------------------------------------------------------|--------------------------------------------|-------|--------|-----------|
| ani-nahida | animefull-latest | <img src="https://github.com/7eu7d7/DreamArtist-sd-webui-extension/blob/master/imgs/pre/nahida.jpg" width = "80" height = "80" alt=""/> | 3, 6 | 8000 | 0.0025 | 3 |
| ani-cocomi | animefull-latest | <img src="https://github.com/7eu7d7/DreamArtist-sd-webui-extension/blob/master/imgs/pre/cocomi.jpg" width = "80" height = "80" alt=""/> | 3, 6 | 8000 | 0.0025 | 3 |
| ani-gura | animefull-latest | <img src="https://github.com/7eu7d7/DreamArtist-sd-webui-extension/blob/master/imgs/pre/gura.jpg" width = "80" height = "80" alt=""/> | 3, 6 | 12000 | 0.0025 | 3 |
| ani-g | animefull-latest | <img src="https://github.com/7eu7d7/DreamArtist-sd-webui-extension/blob/master/imgs/pre/g.Excerpt of 5,790 characters
Read on GitHub
RainbowNeko
9
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:2f397b252fac5a22, name:stable diffusion, desc:stable diffusion