Instructions to use ashllay/noobai-control-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ashllay/noobai-control-lora with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("ashllay/noobai-control-lora") pipe = StableDiffusionControlNetPipeline.from_pretrained( "Laxhar/sdxl_noob", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 05607723a241d2b900bb3eccacb8e1a2aaea83843c44f87b7a2bf896a5f3532e
- Size of remote file:
- 774 MB
- SHA256:
- 4c6932ba3e304b52e425800948a074f56d1bcd3932fa515cfd8056707a7c1525
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.