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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 1e6d855d343a65445f455cb4230f685e554549881c15121176048a2f61b11c1e
- Size of remote file:
- 3.44 GB
- SHA256:
- 56afd34c05a153aec419a4a5516da3b1dce24e62bf4bc9ced88a7298fe7d6973
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