Instructions to use Taimoor-R/model_out with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Taimoor-R/model_out with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("Taimoor-R/model_out") pipe = StableDiffusionControlNetPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 4482ed1e0617c933dcd6b0e267581aef9da472916ea8c8fd9df0c566c839b7f8
- Size of remote file:
- 2.89 GB
- SHA256:
- 43ad008194a0df2cb054c7a0c2e5a0748571ff307b1a0e6244376da8f05a692a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.