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. | | |