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
| # DualCLIPLoaderGGUFMultiGPU | |
| The `DualCLIPLoaderGGUFMultiGPU` node is used to load dual GGUF format CLIP text encoder models with device selection capability, enabling users to specify which GPU or device should be used for model execution. | |
| This node automatically detects models located in the `ComfyUI/models/clip` and `ComfyUI/models/clip_gguf` folders, and it will also read models from additional paths configured in the `extra_model_paths.yaml` file. Sometimes, you may need to **refresh the ComfyUI interface** to allow it to read the model files from the corresponding folder. | |
| ## Inputs | |
| | Parameter | Data Type | Description | | |
| | --- | --- | --- | | |
| | `clip_name1` | `STRING` | The name of the first CLIP model to load from combined clip and clip_gguf folders. | | |
| | `clip_name2` | `STRING` | The name of the second CLIP model to load from combined clip and clip_gguf folders. | | |
| | `type` | `STRING` | The type of CLIP model configuration for dual loading. | | |
| | `device` | `STRING` | Target device for text encoder compute operations (e.g., 'cuda:0', 'cuda:1', 'cpu'). Selected from available devices on your system. | | |
| ## Outputs | |
| | Output Name | Data Type | Description | | |
| | --- | --- | --- | | |
| | `CLIP` | `CLIP` | The loaded dual CLIP text encoder models. | | |