Instructions to use killah-t-cell/boxes_cn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use killah-t-cell/boxes_cn with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("killah-t-cell/boxes_cn") pipe = StableDiffusionControlNetPipeline.from_pretrained( "stabilityai/stable-diffusion-2-1-base", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-8000/controlnet/diffusion_pytorch_model.bin from killah-t-cell/boxes_cn: direct link, hf CLI and curl.
- Browser
- Download file 1.46 GB
-
https://huggingface.co/killah-t-cell/boxes_cn/resolve/main/checkpoint-8000/controlnet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://killah-t-cell/boxes_cn/checkpoint-8000/controlnet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/killah-t-cell/boxes_cn/resolve/main/checkpoint-8000/controlnet/diffusion_pytorch_model.bin
1.46 GB
- Xet hash:
- ee7265d3025c331509ae782f0f9b60d6c2c154d15cc03330b720dd50bff0293b
- Size of remote file:
- 1.46 GB
- SHA256:
- 44582a20461ff087100df2a77ad55fe991dcfb917c9dbc9d1e6fd11d8c4acaa6
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