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
LoadWanVideoClipTextEncoderMultiGPU
LoadWanVideoClipTextEncoderMultiGPU loads WanVideo CLIP vision/text encoders on the device you specify, making it easy to keep encoders off your primary compute GPU when memory is tight.
Inputs
Required
| Parameter | Data Type | Description |
|---|---|---|
model_name |
STRING |
CLIP vision or text encoder model from ComfyUI/models/clip_vision or ComfyUI/models/text_encoders. |
precision |
STRING |
Weight precision for the model (fp16, fp32, or bf16). |
Optional
| Parameter | Data Type | Description |
|---|---|---|
device |
STRING |
Target MultiGPU device to host the encoder. |
Outputs
| Output Name | Data Type | Description |
|---|---|---|
wan_clip_vision |
CLIP_VISION |
Loaded CLIP vision/text module ready for image conditioning. |
load_device |
MULTIGPUDEVICE |
Device that now owns the encoder; feed into WanVideoClipVisionEncode. |