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
DownloadAndLoadWav2VecModelMultiGPU
DownloadAndLoadWav2VecModelMultiGPU downloads a preset Wav2Vec2 checkpoint from Hugging Face (if missing) and loads it onto the device you choose, mirroring WanVideo's helper while adding MultiGPU awareness.
Inputs
Required
| Parameter | Data Type | Description |
|---|---|---|
model |
STRING |
Preset identifier (TencentGameMate/chinese-wav2vec2-base or facebook/wav2vec2-base-960h). |
base_precision |
STRING |
Weight precision (fp32, bf16, fp16). |
load_device |
STRING |
Wan loader slot (main_device or offload_device). |
device |
STRING |
MultiGPU device to run the audio model. |
Outputs
| Output Name | Data Type | Description |
|---|---|---|
wav2vec_model |
WAV2VECMODEL |
Downloaded and loaded Wav2Vec2 model. |