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
| # LoadFluxControlNetMultiGPU | |
| `LoadFluxControlNetMultiGPU` exposes device selection for XLabAI's FLUX ControlNet loader, letting you keep the ControlNet on a secondary GPU or the CPU while the main FLUX UNet stays on your primary compute device. | |
| ## Inputs | |
| All inputs from the upstream `LoadFluxControlNet` node remain unchanged. The MultiGPU variant introduces one optional field: | |
| | Parameter | Data Type | Description | | |
| | --- | --- | --- | | |
| | `device` | `STRING` | MultiGPU device that will host the ControlNet during inference. | | |
| ## Outputs | |
| Outputs match the base FLUX ControlNet loader exactly; only the device placement differs. | |