Instructions to use CrucibleAI/ControlNetMediaPipeFace with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CrucibleAI/ControlNetMediaPipeFace with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("CrucibleAI/ControlNetMediaPipeFace") pipe = StableDiffusionControlNetPipeline.from_pretrained( "stabilityai/stable-diffusion-2-1-base", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
Download diffusion_sd15/diffusion_pytorch_model.fp16.bin from CrucibleAI/ControlNetMediaPipeFace: direct link, hf CLI and curl.
- Browser
- Download file 723 MB
-
https://huggingface.co/CrucibleAI/ControlNetMediaPipeFace/resolve/main/diffusion_sd15/diffusion_pytorch_model.fp16.bin
- Command line
-
hf download hf://CrucibleAI/ControlNetMediaPipeFace/diffusion_sd15/diffusion_pytorch_model.fp16.bin
-
curl -L -o diffusion_pytorch_model.fp16.bin https://huggingface.co/CrucibleAI/ControlNetMediaPipeFace/resolve/main/diffusion_sd15/diffusion_pytorch_model.fp16.bin
723 MB
- Xet hash:
- 47b08273fa7b5e0a775747bdbd0115744a2f128dae291b71d489e66c22a36d11
- Size of remote file:
- 723 MB
- SHA256:
- 0c37b3dd41e956160909129b50f84fd938116550727b491192cbdbe6f896cd7b
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.