Text-to-Image
Diffusers
Safetensors
stable-diffusion
stable-diffusion-diffusers
controlnet
diffusers-training
Instructions to use Lam-Hung/controlnet_depth_interior with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Lam-Hung/controlnet_depth_interior with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("Lam-Hung/controlnet_depth_interior") pipe = StableDiffusionControlNetPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-8000/optimizer.bin from Lam-Hung/controlnet_depth_interior: direct link, hf CLI and curl.
- Browser
- Download file 725 MB
-
https://huggingface.co/Lam-Hung/controlnet_depth_interior/resolve/main/checkpoint-8000/optimizer.bin
- Command line
-
hf download hf://Lam-Hung/controlnet_depth_interior/checkpoint-8000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/Lam-Hung/controlnet_depth_interior/resolve/main/checkpoint-8000/optimizer.bin
725 MB
- Xet hash:
- c06b2dedd6e5c037ab90380f4a3a5848fe6a940066abb033513b3c44c6a9174e
- Size of remote file:
- 725 MB
- SHA256:
- e4e4ee61ea15132f7480376a71d1a5a9ada397b282ecbb8c67c1ca0b026a5500
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