Instructions to use dx8152/Qwen-Image-Edit-2509-Relight with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use dx8152/Qwen-Image-Edit-2509-Relight 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-2509", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("dx8152/Qwen-Image-Edit-2509-Relight") 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
- Local Apps Settings
- Draw Things

- Xet hash:
- c75353b0c63410cde68995814b1f01fba49134030b0281ec912c3f02a45a2d5a
- Size of remote file:
- 3.23 MB
- SHA256:
- 69cbceeecafab7a88cb04f62be039d16c120c5914bae473f5118ff30493cd5a2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.