Instructions to use thedeoxen/MOSS-Image-scribble-controlnet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use thedeoxen/MOSS-Image-scribble-controlnet with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("thedeoxen/MOSS-Image-scribble-controlnet") pipe = StableDiffusionControlNetPipeline.from_pretrained( "OpenMOSS-Team/MOSS-Image-SFT", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
Download NOTICE from thedeoxen/MOSS-Image-scribble-controlnet: direct link, hf CLI and curl.
- Browser
- Download file 262 Bytes
-
https://huggingface.co/thedeoxen/MOSS-Image-scribble-controlnet/resolve/main/NOTICE
- Command line
-
hf download hf://thedeoxen/MOSS-Image-scribble-controlnet/NOTICE
-
curl -L -o NOTICE https://huggingface.co/thedeoxen/MOSS-Image-scribble-controlnet/resolve/main/NOTICE
262 Bytes
| MOSS-Image-SFT control LoRA | |
| Base model: OpenMOSS-Team/MOSS-Image-SFT by OpenMOSS, Apache License 2.0. | |
| Adapter training and release preparation: thedeoxen. | |
| This distribution contains separately trained LoRA adapter weights; no base model weights are bundled. | |