Instructions to use Qwen/Qwen-Image-Edit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Qwen/Qwen-Image-Edit 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", dtype=torch.bfloat16, device_map="cuda") 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] - Inference
- Notebooks
- Google Colab
- Kaggle
DiffSynth-Studio Support
#10
by Artiprocher - opened
We have integrated support for the Qwen-Image-Edit model in DiffSynth-Studio, including features such as VRAM management and LoRA training. Feel free to try it out!
https://github.com/modelscope/DiffSynth-Studio/tree/main/examples/qwen_image
@Artiprocher can you share the example dataset of how to train loras for qwen image edit? and Please add UI to DiffSynth-Studio