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
File size: 429 Bytes
b6acc0a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | {
"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"
} |