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
Upload config.json with huggingface_hub
Browse files- config.json +10 -5
config.json
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}
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{
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"model_type": "custom_qwen_image",
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"architectures": [
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"QwenImageTransformer2DModel"
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],
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"name_or_path": "QuantFunc/Qwen-Image-Edit-Series",
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"task": "image-editing",
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"framework": "quantfunc",
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"license": "other",
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"description": "Pre-quantized Qwen-Image-Edit image editing model series by QuantFunc",
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"_comment": "This is a minimal config to enable download stats on HF Hub. Not used for loading."
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}
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