Instructions to use lightx2v/Qwen-Image-Edit-2511-Lightning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use lightx2v/Qwen-Image-Edit-2511-Lightning with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Qwen/Qwen-Image-Edit-2511", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("lightx2v/Qwen-Image-Edit-2511-Lightning") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Diffusion Single File
How to use lightx2v/Qwen-Image-Edit-2511-Lightning with Diffusion Single File:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
8-step lora?
I see that you have several 4-step lightning options. Will you be adding 8-step options? The 8-step version always gave me better results, so I'm hoping you'll make one for this new Qwen Edit—unless you think the 4-step is already great.
Steps 4 and 8 are both applicable
@97Buckeye
Hi,
We will release a 8-step version, before that, you may use 8-step inference for this 4-step model.
@97Buckeye
Hi,
We will release a 8-step version, before that, you may use 8-step inference for this 4-step model.
Hi, is it possible to fix the fp8 model ? Not working on comfyUI
qwen_image_edit_2511_fp8_e4m3fn_scaled_lightning_comfyui.safetensors
+1 , images gets red hue added for some reason with 4 steps , could be just 2511 tho
@siraxe Maybe you are using workflow from 2509. For 2511 you also need to add "FluxKontextMultiReferenceLatentMethod" node to positive and negative conditionings
@97Buckeye
Hi,
We will release a 8-step version, before that, you may use 8-step inference for this 4-step model
I cant find any info regarding this but gpt suggested that if the distill lora been trained for specific steps adding extra steps or lowering the lora strength might be an issue, but i see in community some users lower the lora strength and add few extra steps, can you please confirm on both cases. if its normal to play with strength and add extra steps?
thanks for the 8 steps.. 4 steps is not usable at all its like Q2 gguf 😁🤣