Instructions to use lightx2v/Qwen-Image-Lightning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lightx2v/Qwen-Image-Lightning with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Qwen/Qwen-Image", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("lightx2v/Qwen-Image-Lightning") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
workflow for Qwen-Image-Edit-Lightning-4steps
#15
by Alan8989 - opened
Hello, please share the workflow for Qwen-Image-Edit-Lightning-4steps
Hello, please share the workflow for Qwen-Image-Edit-Lightning-4steps
Hi, we have uploaded the workflow for Qwen-Image-Edit with lightning loras, please check https://github.com/ModelTC/Qwen-Image-Lightning/tree/main/workflows.
I probably miss something, but how do you control output resolution in qwen edit, or is it always 1024x1024? It's very important for my slow hardware. Maybe i need a better workflow.