Instructions to use bbbboiwow/cocccck with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use bbbboiwow/cocccck with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("bbbboiwow/cocccck", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
DiffControlNetLoaderMultiGPU
The DiffControlNetLoaderMultiGPU node is used to load Diffusers ControlNet models (HuggingFace Hub repositories) with device selection capability, enabling users to specify which GPU or device should be used for model execution.
This node loads ControlNet models directly from HuggingFace model repositories by specifying the repository ID (e.g., "diffusers/controlnet-canny-sdxl-1.0").
Inputs
| Parameter | Data Type | Description |
|---|---|---|
model_path |
STRING |
The HuggingFace repository ID or local path of the diffusers ControlNet model to load. |
device |
STRING |
Target device for compute operations (e.g., 'cuda:0', 'cuda:1', 'cpu'). Selected from available devices on your system. |
Outputs
| Output Name | Data Type | Description |
|---|---|---|
CONTROL_NET |
CONTROL_NET |
The loaded diffusers ControlNet model. |