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
Joseph Catrambone
Rename controlnet_* to be consistent with ControlNet1.1 model naming scheme.
6948da2 Download control_v2p_sd15_mediapipe_face.full.ckpt from CrucibleAI/ControlNetMediaPipeFace: direct link, hf CLI and curl.
- Browser
- Download file 8.6 GB
-
https://huggingface.co/CrucibleAI/ControlNetMediaPipeFace/resolve/main/control_v2p_sd15_mediapipe_face.full.ckpt
- Command line
-
hf download hf://CrucibleAI/ControlNetMediaPipeFace/control_v2p_sd15_mediapipe_face.full.ckpt
-
curl -L -o control_v2p_sd15_mediapipe_face.full.ckpt https://huggingface.co/CrucibleAI/ControlNetMediaPipeFace/resolve/main/control_v2p_sd15_mediapipe_face.full.ckpt
8.6 GB
- Xet hash:
- 33463fc198f5f2b67b25ee954f6cffd576f7c3eefb4af95987085901a80a5441
- Size of remote file:
- 8.6 GB
- SHA256:
- a2a71953d7372d5585899b44693a7532ebbf80c091108ae2b8987ca93cc2dac2
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