Instructions to use OPPOer/Qwen-Image-Edit-2509-Pruning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use OPPOer/Qwen-Image-Edit-2509-Pruning 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("OPPOer/Qwen-Image-Edit-2509-Pruning", 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] - Notebooks
- Google Colab
- Kaggle
Update README.md
#2
by jschoormans - opened
README.md
CHANGED
|
@@ -74,7 +74,7 @@ import os
|
|
| 74 |
import torch
|
| 75 |
from PIL import Image
|
| 76 |
from diffusers import QwenImageEditPlusPipeline
|
| 77 |
-
model_name = f"OPPOer/Qwen-Image-Edit-2509-
|
| 78 |
pipeline = QwenImageEditPlusPipeline.from_pretrained(model_name, torch_dtype=torch.bfloat16)
|
| 79 |
print("pipeline loaded")
|
| 80 |
pipeline.to('cuda')
|
|
|
|
| 74 |
import torch
|
| 75 |
from PIL import Image
|
| 76 |
from diffusers import QwenImageEditPlusPipeline
|
| 77 |
+
model_name = f"OPPOer/Qwen-Image-Edit-2509-13B-4steps"
|
| 78 |
pipeline = QwenImageEditPlusPipeline.from_pretrained(model_name, torch_dtype=torch.bfloat16)
|
| 79 |
print("pipeline loaded")
|
| 80 |
pipeline.to('cuda')
|