Instructions to use killah-t-cell/model_out with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use killah-t-cell/model_out with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("killah-t-cell/model_out") pipe = StableDiffusionControlNetPipeline.from_pretrained( "stabilityai/stable-diffusion-2-1-base", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-5000/controlnet/diffusion_pytorch_model.bin from killah-t-cell/model_out: direct link, hf CLI and curl.
- Browser
- Download file 1.46 GB
-
https://huggingface.co/killah-t-cell/model_out/resolve/main/checkpoint-5000/controlnet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://killah-t-cell/model_out/checkpoint-5000/controlnet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/killah-t-cell/model_out/resolve/main/checkpoint-5000/controlnet/diffusion_pytorch_model.bin
1.46 GB
- Xet hash:
- bfef5110c7b5f9c25431df75bd509017b5307691a7529acb5af0d04bdab721e9
- Size of remote file:
- 1.46 GB
- SHA256:
- f63921365be4d218b388cc566ae7f2f6672e2faf07bc374527d7c078d6bc820f
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