Instructions to use Nahrawy/controlnet-vidit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Nahrawy/controlnet-vidit with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("Nahrawy/controlnet-vidit") pipe = StableDiffusionControlNetPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download 8000/diffusion_flax_model.msgpack from Nahrawy/controlnet-vidit: direct link, hf CLI and curl.
- Browser
- Download file 1.45 GB
-
https://huggingface.co/Nahrawy/controlnet-vidit/resolve/main/8000/diffusion_flax_model.msgpack
- Command line
-
hf download hf://Nahrawy/controlnet-vidit/8000/diffusion_flax_model.msgpack
-
curl -L -o diffusion_flax_model.msgpack https://huggingface.co/Nahrawy/controlnet-vidit/resolve/main/8000/diffusion_flax_model.msgpack
1.45 GB
- Xet hash:
- a47c28ee254fdbe12d3b0e4381a0e2f444206288fcc5886c99d8bb45911ba17b
- Size of remote file:
- 1.45 GB
- SHA256:
- db420b60623bcaad9a8d32056b54d0d97652f30ff5e098549949c0aa9849d391
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