Instructions to use ParityError/ControlNet-Shadows with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ParityError/ControlNet-Shadows with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("ParityError/ControlNet-Shadows") pipe = StableDiffusionControlNetPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download diffusion_flax_model.msgpack from ParityError/ControlNet-Shadows: direct link, hf CLI and curl.
- Browser
- Download file 1.45 GB
-
https://huggingface.co/ParityError/ControlNet-Shadows/resolve/main/diffusion_flax_model.msgpack
- Command line
-
hf download hf://ParityError/ControlNet-Shadows/diffusion_flax_model.msgpack
-
curl -L -o diffusion_flax_model.msgpack https://huggingface.co/ParityError/ControlNet-Shadows/resolve/main/diffusion_flax_model.msgpack
1.45 GB
- Xet hash:
- 7822300872ff9e9bcc050c6d6508f22dfecef8226be38d0b7d6b68a4033fb095
- Size of remote file:
- 1.45 GB
- SHA256:
- 0b97cdc9d257e7ccba93c73f75030bea287ff3ccf0c1294531dcddaf3634cb4f
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