Text-to-Image
Diffusers
Safetensors
English
CRSDiffPipeline
remote-sensing
diffusion
controlnet
custom-pipeline
Instructions to use BiliSakura/CRS-Diff with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BiliSakura/CRS-Diff with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("BiliSakura/CRS-Diff") pipe = StableDiffusionControlNetPipeline.from_pretrained( "fill-in-base-model", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
- Xet hash:
- b03daa8a3be59dd1c6f79b516a4c183cb1c1419be381134abcca6c39015575a6
- Size of remote file:
- 492 MB
- SHA256:
- 651247bce4134453769880497b0ff59124fe047ee7cd7c91ed55308e6503195d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.