Instructions to use FlyingFishzzz/model_out with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use FlyingFishzzz/model_out with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("FlyingFishzzz/model_out") pipe = StableDiffusionControlNetPipeline.from_pretrained( "stabilityai/stable-diffusion-2-1-base", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee

- Xet hash:
- 90049a01d7bf628628cc8dc8a08970cddcf64ba04d03ac39488ce12fc9ccafe0
- Size of remote file:
- 1.38 MB
- SHA256:
- cf48cd8d04154b9ad8908e9d30a9f209a55ea8ce18a2b9e0d6e8c983e21f01a9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.