sdxs-2b / README.md
recoilme's picture
alpha
44d6264
---
license: other
license_name: modified-mit
license_link: https://huggingface.co/AiArtLab/sdxs-2b/blob/main/LICENSE
pipeline_tag: text-to-image
widget:
- text: sdxs-2b
output:
url: media/refined.jpg
---
# Simple Diffusion XS (sdxs-2b alpha version)
*XS Size, Excess Quality*
Train status: 4xRTX5090 / we need more gold / [support us please..](https://huggingface.co/AiArtLab/sdxs-2b#donations)
At AiArtLab, we strive to create a free, compact and fast model that can be trained on consumer graphics cards.
- CosmosTransformer3D: 2b parameters
- Qwen3.5: 0.8b parameters
- Qwen vae: 16ch8x
- Resolution: Default 768x1152, trained from 576 to 1152 with step 64
- Limitations: trained on small datasets ~2.5kk, focused on art / illustrations / anime and photo
- Captions: danbooru, natural (short/medium), trained with 250 max toks
### Key points
<img src="media/start.png" height="256"/>
- Apr 2026: Started research of Cosmos Transformer
- May 2026: 1st preview (Initial model weights)
- May 2026: finetuned Qwen3.5-0.8B
- May 2026: hybrid EDM/Karras scheduler
- May 2026: img2img pipeline and txt2video pipeline (not trained)
- May 2026: [telegram bot](https://t.me/inkimpbot)
### Random samples
![promo](media/result_grid.jpg)
### Text 2 image
```python
#!pip install -U torch torchvision
#!pip install -U diffusers accelerate transformers
import torch
from diffusers import DiffusionPipeline
device = "cuda" if torch.cuda.is_available() else "cpu"
dtype = torch.bfloat16 if torch.cuda.is_available() else torch.float32
pipe_id = "AiArtLab/sdxs-2b"
pipe = DiffusionPipeline.from_pretrained(
pipe_id,
torch_dtype=dtype,
trust_remote_code=True
).to(device)
refined = "A blonde-haired Red Eyes girl with a hair ribbon, half-updo, and tsurime stands solo in a flower field holding a bouquet with a serene smile, wearing green overalls, a white shirt, rolled-up sleeves, and a straw hat with a flower while looking at the viewer under volumetric and natural lighting with a Dutch angle."
negative_prompt = "low quality, bad quality, blurry, sketch, sepia, text, bad anatomy, bad proportions, bad hands, missing fingers, child drawing"
output = pipe(
prompt=refined,
negative_prompt=negative_prompt,
)
image = output.images[0]
image.show()
```
### Prompt refiner
```python
refined = pipe.refine_prompts("1girl")
print(refined[0])
```
## Donations
Donated: 25$
Thanks for your support!
- Euro / dollars: sorry, we can’t accept payments via Patreon or Ko-fi. Please register on [vast.ai](https://cloud.vast.ai/billing/) (this is the GPU provider we use for training the model), top up any amount, and transfer: Transfer Money / User / Email: vadim-kulibaba@yandex.ru.
- RUB: [donate in rub](https://www.tbank.ru/cf/90ensBQqpJj)
- DOGE: DEw2DR8C7BnF8GgcrfTzUjSnGkuMeJhg83
- BTC: 3JHv9Hb8kEW8zMAccdgCdZGfrHeMhH1rpN
- USDT
- Ethereum / Polygon / BNB SmartChain: 0xD4388B6698dFaE1460E72099D4F208aaCA4f6E6C
- Tron: TD7ey4h9igPGdcrcBcnZaz56R5tNgRZNvV
- Solana: MMYFJeYEtYHrSNFHChytJDHbEDniXrnAxPNLhJ1LbkB
## Contacts
Please contact with us if you may provide some GPU's or money on training
- telegram [recoilme](https://t.me/recoilme) *prefered way
- mail at aiartlab.org (slow response)
## Citation
```bibtex
@misc{sdxs,
title={Simple Diffusion XS-2b},
author={recoilme and AiArtLab Team},
url={https://huggingface.co/AiArtLab/sdxs-2b},
year={2026}
}
```