Instructions to use peteromallet/Qwen-Image-Edit-InStyle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use peteromallet/Qwen-Image-Edit-InStyle 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("Qwen/Qwen-Image-Edit", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("peteromallet/Qwen-Image-Edit-InStyle") 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] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
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README.md
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- Capturing subtle style nuances from reference images
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- Avoiding unwanted detail transplantation from source images
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- Generating coherent images that match the intended style
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The model may struggle with:
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- Extremely abstract or unconventional artistic styles
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- Very specific technical details that conflict with the reference style
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## Training Data
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- Capturing subtle style nuances from reference images
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- Avoiding unwanted detail transplantation from source images
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- Generating coherent images that match the intended style
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- Strong prompt adherence
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The model may struggle with:
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- Extremely abstract or unconventional artistic styles
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- Very specific technical details that conflict with the reference style
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- Occasional anatomy issues
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## Training Data
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