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: 424 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 | {
"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"
} |