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
| # MMAudioModelLoaderMultiGPU | |
| `MMAudioModelLoaderMultiGPU` loads MMAudio diffusion checkpoints while letting you pin the model weights to a specific compute device. Use it to keep long-running audio generations off your primary image GPU. | |
| ## Inputs | |
| ### Required | |
| | Parameter | Data Type | Description | | |
| | --- | --- | --- | | |
| | `mmaudio_model` | `STRING` | Model filename from `ComfyUI/models/mmaudio`. | | |
| | `base_precision` | `STRING` | Weight precision to request (`fp16`, `fp32`, `bf16`). | | |
| ### Optional | |
| | Parameter | Data Type | Description | | |
| | --- | --- | --- | | |
| | `device` | `STRING` | Target device for the loaded model (e.g. `cuda:0`, `cpu`). | | |
| ## Outputs | |
| | Output Name | Data Type | Description | | |
| | --- | --- | --- | | |
| | `mmaudio_model` | `MMAUDIO_MODEL` | Loaded MMAudio diffusion pipeline. | | |