Instructions to use DionTimmer/controlnet_qrcode with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use DionTimmer/controlnet_qrcode with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("DionTimmer/controlnet_qrcode") pipe = StableDiffusionControlNetPipeline.from_pretrained( "fill-in-base-model", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
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# QR Code Conditioned ControlNet Models for Stable Diffusion 1.5 and 2.1
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## Model Description
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These ControlNet models have been trained on a large dataset of 150,000 QR code + QR code artwork couples. They provide a solid foundation for generating QR code-based artwork that is aesthetically pleasing, while still maintaining the integral QR code shape.
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# QR Code Conditioned ControlNet Models for Stable Diffusion 1.5 and 2.1
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## Model Description
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These ControlNet models have been trained on a large dataset of 150,000 QR code + QR code artwork couples. They provide a solid foundation for generating QR code-based artwork that is aesthetically pleasing, while still maintaining the integral QR code shape.
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