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
| { | |
| "embed_dim": 4, | |
| "monitor": "val/rec_loss", | |
| "ddconfig": { | |
| "double_z": true, | |
| "z_channels": 4, | |
| "resolution": 256, | |
| "in_channels": 3, | |
| "out_ch": 3, | |
| "ch": 128, | |
| "ch_mult": [ | |
| 1, | |
| 2, | |
| 4, | |
| 4 | |
| ], | |
| "num_res_blocks": 2, | |
| "attn_resolutions": [], | |
| "dropout": 0.0 | |
| }, | |
| "lossconfig": { | |
| "target": "torch.nn.Identity" | |
| }, | |
| "_target": "crs_core.autoencoder.AutoencoderKL" | |
| } |