Text-to-Image
Diffusers
StableDiffusionControlNetPipeline
stable-diffusion
stable-diffusion-diffusers
controlnet
Instructions to use krea/aesthetic-controlnet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use krea/aesthetic-controlnet with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("krea/aesthetic-controlnet") pipe = StableDiffusionControlNetPipeline.from_pretrained( "fill-in-base-model", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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# Aesthetic ControlNet
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This model can produce highly aesthetic results from an input image and text prompt.
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ControlNet is a method that can be used to condition diffusion models on arbitrary input features, such as image edges, segmentation maps, or human poses.
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# Aesthetic ControlNet
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This model can produce highly aesthetic results from an input image and a text prompt.
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ControlNet is a method that can be used to condition diffusion models on arbitrary input features, such as image edges, segmentation maps, or human poses.
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