Text-to-Image
Diffusers
Safetensors
stable-diffusion
stable-diffusion-diffusers
controlnet
diffusers-training
Instructions to use SS-max/controlnet_too_simple_SAM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SS-max/controlnet_too_simple_SAM with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("SS-max/controlnet_too_simple_SAM") pipe = StableDiffusionControlNetPipeline.from_pretrained( "stabilityai/stable-diffusion-2-1-base", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download diffusion_pytorch_model.safetensors from SS-max/controlnet_too_simple_SAM: direct link, hf CLI and curl.
- Browser
- Download file 1.46 GB
-
https://huggingface.co/SS-max/controlnet_too_simple_SAM/resolve/main/diffusion_pytorch_model.safetensors
- Command line
-
hf download hf://SS-max/controlnet_too_simple_SAM/diffusion_pytorch_model.safetensors
-
curl -L -o diffusion_pytorch_model.safetensors https://huggingface.co/SS-max/controlnet_too_simple_SAM/resolve/main/diffusion_pytorch_model.safetensors
1.46 GB
- Xet hash:
- f103c0256eaa75b488c3efc653e3847258664002babd9ef1f1758d1163d6ecbe
- Size of remote file:
- 1.46 GB
- SHA256:
- 71b0768fe274a7e74e7da7426fdad1c2ef73f5007156563323fdcc34569372ce
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