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-4000/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-4000/optimizer.bin
- Command line
-
hf download hf://Lam-Hung/controlnet_depth_interior/checkpoint-4000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/Lam-Hung/controlnet_depth_interior/resolve/main/checkpoint-4000/optimizer.bin
725 MB
- Xet hash:
- e060b13c0978652ef5ef694af8baa7452c3403a008bc721ce6ef94ec38fa5ccf
- Size of remote file:
- 725 MB
- SHA256:
- f97f79db8dd0129b8979e910a94aa3a03f407e8bd3ce71fd48d66443b8df2707
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