Instructions to use AiArtLab/sdxs-2b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AiArtLab/sdxs-2b with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("AiArtLab/sdxs-2b", dtype=torch.bfloat16, device_map="cuda") prompt = "sdxs-2b" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
metadata
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..
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
- 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
Random samples
Text 2 image
#!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
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 (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
- 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 *prefered way
- mail at aiartlab.org (slow response)
Citation
@misc{sdxs,
title={Simple Diffusion XS-2b},
author={recoilme and AiArtLab Team},
url={https://huggingface.co/AiArtLab/sdxs-2b},
year={2026}
}
