Instructions to use Abhi5ingh/ControlnetDresscode with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Abhi5ingh/ControlnetDresscode with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("Abhi5ingh/ControlnetDresscode") pipe = StableDiffusionControlNetPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
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# controlnet-Abhi5ingh/model_dresscode
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These are controlnet weights trained on runwayml/stable-diffusion-v1-5 with a new type of conditioning on sketch and text.
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You can find the results and the validation inference below
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Results:
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# controlnet-Abhi5ingh/model_dresscode
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These are controlnet weights trained on runwayml/stable-diffusion-v1-5 with a new type of conditioning on sketch and text.
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You can find the results and the validation inference below:
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Results:
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