Instructions to use thedeoxen/Krea-2-pose-controlnet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use thedeoxen/Krea-2-pose-controlnet with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("thedeoxen/Krea-2-pose-controlnet") pipe = StableDiffusionControlNetPipeline.from_pretrained( "krea/Krea-2-Turbo", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
.png)
- Xet hash:
- 625e209378bc315a0e747485ddd1cf5a06fdf7c9e0b18d9a6c5a813d9344245f
- Size of remote file:
- 4.36 MB
- SHA256:
- dba1e86c5ed38f9d12a4163d5c2969faa7acab4ecdf669e6c146283fdf02dbab
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.