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 4500/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/4500/diffusion_flax_model.msgpack
- Command line
-
hf download hf://Nahrawy/controlnet-vidit/4500/diffusion_flax_model.msgpack
-
curl -L -o diffusion_flax_model.msgpack https://huggingface.co/Nahrawy/controlnet-vidit/resolve/main/4500/diffusion_flax_model.msgpack
1.45 GB
- Xet hash:
- 22b341457196dc518dfdaf01366d1b66d6c2acf7b326f287407b970ed30cd774
- Size of remote file:
- 1.45 GB
- SHA256:
- 19789ed201b14253f89fe651f5fcc1338f6cdb72d31c06125af2d17cb3153eb7
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