Image-to-Image
Diffusers
Safetensors
StableDiffusionControlNetCCSRPipeline
image-super-resolution
controlnet
stable-diffusion
ccsr
Instructions to use kharma1/ccsr_v2_repost with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use kharma1/ccsr_v2_repost with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("kharma1/ccsr_v2_repost") pipe = StableDiffusionControlNetPipeline.from_pretrained( "stabilityai/stable-diffusion-2-1-base,isometricneko/stable-diffusion-v2.1-clone", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
File size: 599 Bytes
65c51e4 | 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 26 27 28 29 30 31 32 33 | {
"_class_name": "StableDiffusionControlNetCCSRPipeline",
"_class_module": "ccsr.pipelines.pipeline_ccsr",
"_diffusers_version": "0.39.0",
"controlnet": [
"ccsr.models.controlnet",
"ControlNetCCSRModel"
],
"feature_extractor": [
"transformers",
"CLIPImageProcessor"
],
"scheduler": [
"diffusers",
"DDPMScheduler"
],
"text_encoder": [
"transformers",
"CLIPTextModel"
],
"tokenizer": [
"transformers",
"CLIPTokenizer"
],
"unet": [
"diffusers",
"UNet2DConditionModel"
],
"vae": [
"diffusers",
"AutoencoderKL"
]
} |