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
| { | |
| "image_size": 32, | |
| "in_channels": 4, | |
| "model_channels": 320, | |
| "out_channels": 4, | |
| "num_res_blocks": 2, | |
| "attention_resolutions": [ | |
| 4, | |
| 2, | |
| 1 | |
| ], | |
| "channel_mult": [ | |
| 1, | |
| 2, | |
| 4, | |
| 4 | |
| ], | |
| "use_checkpoint": true, | |
| "num_heads": 8, | |
| "use_spatial_transformer": true, | |
| "transformer_depth": 1, | |
| "context_dim": 768, | |
| "legacy": false, | |
| "_target": "crs_core.local_adapter.LocalControlUNetModel" | |
| } |