X-Omni Models
Collection
4 items β’ Updated β’ 5
How to use X-Omni/X-Omni-Zh with Diffusers:
pip install -U diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("X-Omni/X-Omni-Zh", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]π Project Page | π Paper | π»β Code | π HuggingFace Space
If you find this project helpful for your research or use it in your own work, please cite our paper:
@article{geng2025xomni,
author = {Zigang Geng, Yibing Wang, Yeyao Ma, Chen Li, Yongming Rao, Shuyang Gu, Zhao Zhong, Qinglin Lu, Han Hu, Xiaosong Zhang, Linus, Di Wang and Jie Jiang},
title = {X-Omni: Reinforcement Learning Makes Discrete Autoregressive Image Generative Models Great Again},
journal = {CoRR},
volume = {abs/2507.22058},
year = {2025},
}