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
| # MMAudioSamplerMultiGPU | |
| `MMAudioSamplerMultiGPU` renders audio clips with MMAudio while giving you control over which accelerator runs the diffusion loop and whether frames stay offloaded. | |
| ## Inputs | |
| ### Required | |
| | Parameter | Data Type | Description | | |
| | --- | --- | --- | | |
| | `mmaudio_model` | `MMAUDIO_MODEL` | Core MMAudio checkpoint prepared by the loader. | | |
| | `feature_utils` | `MMAUDIO_FEATUREUTILS` | Feature utility bundle containing VAE, Synchformer, CLIP, and optional vocoder. | | |
| | `duration` | `FLOAT` | Target duration for the generated audio in seconds. | | |
| | `steps` | `INT` | Number of sampler iterations to run. | | |
| | `cfg` | `FLOAT` | Classifier-free guidance scale. | | |
| | `seed` | `INT` | Random seed, `0` for deterministic repeatability. | | |
| | `prompt` | `STRING` | Positive conditioning text. | | |
| | `negative_prompt` | `STRING` | Negative conditioning text. | | |
| | `mask_away_clip` | `BOOLEAN` | Hide supplied clip video frames during sampling. | | |
| | `force_offload` | `BOOLEAN` | Force temporary offload of the model after sampling. | | |
| ### Optional | |
| | Parameter | Data Type | Description | | |
| | --- | --- | --- | | |
| | `images` | `IMAGE` | Reference frames to guide the sampler. | | |
| | `device` | `STRING` | Device that hosts the diffusion pass (`cuda:0`, `cpu`, etc.). | | |
| ## Outputs | |
| | Output Name | Data Type | Description | | |
| | --- | --- | --- | | |
| | `audio` | `AUDIO` | Generated audio waveform tensor. | | |