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
CheckpointLoaderNF4MultiGPU
CheckpointLoaderNF4MultiGPU wraps the NF4 checkpoint loader from ComfyUI_bitsandbytes_NF4 so you can pick the execution device when working with 4-bit Quantised diffusion checkpoints.
Inputs
All base parameters from CheckpointLoaderNF4 are retained. The MultiGPU wrapper adds one optional field:
| Parameter | Data Type | Description |
|---|---|---|
device |
STRING |
Device that should own the loaded NF4 checkpoint (GPU id or cpu). |
Outputs
Outputs are identical to the upstream NF4 loader (UNet/CLIP/VAE tuple). The only behavioural change is the explicit device placement. |