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
UNETLoaderMultiGPU
The UNETLoaderMultiGPU node is used to load diffusion model UNet components with device selection capability, enabling users to specify which GPU or device should be used for model execution.
This node automatically detects models located in the ComfyUI/models/unet folder, and it will also read models from additional paths configured in the extra_model_paths.yaml file. Sometimes, you may need to refresh the ComfyUI interface to allow it to read the model files from the corresponding folder.
Inputs
| Parameter | Data Type | Description |
|---|---|---|
unet_name |
STRING |
The name of the UNet 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 |
|---|---|---|
MODEL |
MODEL |
The loaded UNet diffusion model. |