Text-to-Image
Diffusers
Safetensors
stable-diffusion
stable-diffusion-diffusers
controlnet
diffusers-training
Instructions to use sidnarsipur/controlnet_height with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use sidnarsipur/controlnet_height with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("sidnarsipur/controlnet_height") pipe = StableDiffusionControlNetPipeline.from_pretrained( "stabilityai/stable-diffusion-2-1-base", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-4000/optimizer.bin from sidnarsipur/controlnet_height: direct link, hf CLI and curl.
- Browser
- Download file 2.91 GB
-
https://huggingface.co/sidnarsipur/controlnet_height/resolve/main/checkpoint-4000/optimizer.bin
- Command line
-
hf download hf://sidnarsipur/controlnet_height/checkpoint-4000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/sidnarsipur/controlnet_height/resolve/main/checkpoint-4000/optimizer.bin
2.91 GB
- Xet hash:
- 821bd4c979afa93983459acb75147e3ac2e0fe74e65277742307652aed319852
- Size of remote file:
- 2.91 GB
- SHA256:
- fccd964a46b07f0b1b3216da9a3d22ec36e4bc26784d5c1722e13386fedd362c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.