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 2000/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/2000/diffusion_flax_model.msgpack
- Command line
-
hf download hf://Nahrawy/controlnet-vidit/2000/diffusion_flax_model.msgpack
-
curl -L -o diffusion_flax_model.msgpack https://huggingface.co/Nahrawy/controlnet-vidit/resolve/main/2000/diffusion_flax_model.msgpack
1.45 GB
- Xet hash:
- 3593081e18a6cfd34c0431750f5145ad1cdf947ec18d249e3d541af1a31dbe24
- Size of remote file:
- 1.45 GB
- SHA256:
- f91d9d3b9c430dbfa6ad6cdb857b69a1214036e84bc73e5c7757eecccc6c7756
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