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
- Draw Things
- DiffusionBee
Any plan of releasing qwen_image_edit_fp8_e4m3fn_scaled version (not 2509)
#40
by BxJ - opened
As stated in https://github.com/ModelTC/Qwen-Image-Lightning#-using-lightning-loras-with-fp8-models, current FP8 model was a directly downcast version which may generate grid artifacts with lightning LoRAs.
Is there any plan of releasing the scaled version of qwen-image-edit model just like the 2509 version? or any tutorials of how to make a calibrated conversion process with scaling?