Image-to-Image
Diffusers
Safetensors
English
QuantFuncPipeline
custom_qwen_image
image-editing
diffusion
quantized
quantfunc
Instructions to use QuantFunc/Qwen-Image-Edit-Series with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use QuantFunc/Qwen-Image-Edit-Series 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("QuantFunc/Qwen-Image-Edit-Series", 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
File size: 442 Bytes
67ed06c 9a5cc26 67ed06c | 1 2 3 4 5 6 7 8 9 10 11 12 | {
"model_type": "custom_qwen_image",
"architectures": [
"QwenImageTransformer2DModel"
],
"name_or_path": "QuantFunc/Qwen-Image-Edit-Series",
"task": "image-editing",
"framework": "quantfunc",
"license": "other",
"description": "Pre-quantized Qwen-Image-Edit image editing model series by QuantFunc",
"_comment": "This is a minimal config to enable download stats on HF Hub. Not used for loading."
} |