Model Details
Full Model IDlightx2v/Qwen-Image-Lightning
Pipeline / Tasktext-to-image
Librarydiffusers
Downloads (all-time)372.9K
Likes800
Last Modified11/3/2025
Author / Orglightx2v
PrivateNo � public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("text-to-image", model="lightx2v/Qwen-Image-Lightning")
# Run inference
result = pipe("Your input here")
print(result)����� Tags
diffusersQwen-ImagedistillationLoRAloratext-to-imageenzhbase_model:Qwen/Qwen-Imagebase_model:adapter:Qwen/Qwen-Imagelicense:apache-2.0region:us
More Text to Image Models
See all →🚀 Use This Model
Access model files, inference API, and full documentation on Hugging Face.
Open on Hugging Face →Browse Model Files ↗�� Browse All Models🎨 Task: Text to Image
This model is designed for the Text to Image task. Explore more models for this use case.
All Text to Image Models →📊 Popularity
⬇ Downloads372.9K
����� Community Likes800
🛠�� Requirements
- →Install: pip install diffusers
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.