Instructions to use razgaon/model-res with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use razgaon/model-res with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("razgaon/model-res") pipe = StableDiffusionControlNetPipeline.from_pretrained( "stabilityai/stable-diffusion-2-1-base", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-2000/controlnet/diffusion_pytorch_model.bin from razgaon/model-res: direct link, hf CLI and curl.
- Browser
- Download file 1.46 GB
-
https://huggingface.co/razgaon/model-res/resolve/main/checkpoint-2000/controlnet/diffusion_pytorch_model.bin
- Command line
-
hf download hf://razgaon/model-res/checkpoint-2000/controlnet/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/razgaon/model-res/resolve/main/checkpoint-2000/controlnet/diffusion_pytorch_model.bin
1.46 GB
- Xet hash:
- 5c5d222e63533f560a3e4edd8899b20f3f0f6167197e8d9f83878d0c841c66a9
- Size of remote file:
- 1.46 GB
- SHA256:
- 8f31c33700727877216ad83713068e8151f9ee5b1b5c1034e605fde87a3e1b40
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