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
| # DownloadAndLoadFlorence2ModelMultiGPU | |
| `DownloadAndLoadFlorence2ModelMultiGPU` mirrors the download-and-load helper supplied by `ComfyUI-Florence2`, but with explicit device and offload selection so large Florence2 checkpoints can live on secondary GPUs or CPU memory. | |
| ## Inputs | |
| All original inputs from `DownloadAndLoadFlorence2Model` remain available. The MultiGPU wrapper introduces two optional selectors: | |
| | Parameter | Data Type | Description | | |
| | --- | --- | --- | | |
| | `device` | `STRING` | Compute device to host the model once loaded. | | |
| | `offload_device` | `STRING` | Device that receives automatic offloads (defaults to `cpu`). | | |
| ## Outputs | |
| Outputs match the base Florence2 helper (model handle plus aux data). The only difference is that the returned model is already resident on the device you specified. | |