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 1750/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/1750/diffusion_flax_model.msgpack
- Command line
-
hf download hf://ParityError/ControlNet-Shadows/1750/diffusion_flax_model.msgpack
-
curl -L -o diffusion_flax_model.msgpack https://huggingface.co/ParityError/ControlNet-Shadows/resolve/main/1750/diffusion_flax_model.msgpack
1.45 GB
- Xet hash:
- 2ba2418ef883b0f80281c899c86d01d946ff3278b73bc4f827cf7179988c4816
- Size of remote file:
- 1.45 GB
- SHA256:
- d0f5dc6fc3a6489769a9b18c57e6ad0c4411883727de6e1154f1e667ddcf68f4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.