Image-to-Image
Diffusers
Safetensors
QwenImageEditPipeline
sdnq
qwen_image
4-bit precision
8-bit precision
Instructions to use Disty0/Qwen-Image-Edit-SDNQ-uint4-svd-r32 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Disty0/Qwen-Image-Edit-SDNQ-uint4-svd-r32 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("Disty0/Qwen-Image-Edit-SDNQ-uint4-svd-r32", 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
Download processor/merges.txt from Disty0/Qwen-Image-Edit-SDNQ-uint4-svd-r32: direct link, hf CLI and curl.
- Browser
- Download file 1.67 MB
-
https://huggingface.co/Disty0/Qwen-Image-Edit-SDNQ-uint4-svd-r32/resolve/main/processor/merges.txt
- Command line
-
hf download hf://Disty0/Qwen-Image-Edit-SDNQ-uint4-svd-r32/processor/merges.txt
-
curl -L -o merges.txt https://huggingface.co/Disty0/Qwen-Image-Edit-SDNQ-uint4-svd-r32/resolve/main/processor/merges.txt
1.67 MB
File too large to display, you can check the raw version instead.