Instructions to use ovedrive/Qwen-Image-Edit-2511-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ovedrive/Qwen-Image-Edit-2511-4bit 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("ovedrive/Qwen-Image-Edit-2511-4bit", 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
| { | |
| "quantization_method": "mixed_precision_nf4", | |
| "description": "First and last transformer blocks kept at bfloat16, middle layers quantized to NF4", | |
| "high_precision_layers_count": 30, | |
| "note": "Based on city96/Qwen-Image-gguf approach for better quality" | |
| } |