https://github.com/marcoc2/ComfyUI_CogView4-6B_diffusers
Simple wrapper for diffusers inside comfyui
https://github.com/marcoc2/ComfyUI_CogView4-6B_diffusers
Last synced: about 1 month ago
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Simple wrapper for diffusers inside comfyui
- Host: GitHub
- URL: https://github.com/marcoc2/ComfyUI_CogView4-6B_diffusers
- Owner: marcoc2
- Created: 2025-03-04T17:37:14.000Z (about 1 month ago)
- Default Branch: main
- Last Pushed: 2025-03-04T17:43:50.000Z (about 1 month ago)
- Last Synced: 2025-03-04T18:35:05.507Z (about 1 month ago)
- Language: Python
- Size: 0 Bytes
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- awesome-comfyui - **ComfyUI-Cog**
README
# ComfyUI-Cog
- This is a custom node aiming to run CogView4 on diffusers while there is no official implementation on ComfyUI.
- You will need a updated version of diffusers and I don't know if updating it my break other stuff, so I advise you to make in a new instance of ComfyUI
- There is no progress bar preview in this node
## Installation
### Prerequisites
- ComfyUI installed and working
- GPU with at least 8GB VRAM (recommended)
### Installation Steps
1. Clone this repository to your ComfyUI's `custom_nodes` folder:
```bash
cd ComfyUI/custom_nodes
git clone https://github.com/your-username/ComfyUI-Cog
```
2. Install the required dependencies:
```bash
# For standard ComfyUI installation (non-portable):
pip install diffusers transformers accelerate
# To install the latest version of diffusers (recommended):
pip install git+https://github.com/huggingface/diffusers.git
# For ComfyUI Portable:
.\python_embeded\python.exe -m pip install diffusers transformers accelerate
# Or for the latest version of diffusers:
.\python_embeded\python.exe -m pip install git+https://github.com/huggingface/diffusers.git
```
3. Restart ComfyUI
## Usage
After installation, you'll have access to a new node:
### CogView4 Generator
This is the main node that generates images using the CogView4 model.
#### Parameters:
- **prompt**: Text description of the image you want to generate
- **width**: Width of the output image (default: 1024)
- **height**: Height of the output image (default: 1024)
- **num_inference_steps**: Number of inference steps (default: 50)
- **guidance_scale**: Model guidance scale (default: 3.5)
- **num_images**: Number of images to generate per execution (default: 1)
- **seed**: (Optional) Seed for reproducible results
#### Note about Progress Bar:
The CogView4 model does not support progress callbacks, so there is no real-time progress bar available during generation. You will see console output when generation starts and finishes, but no step-by-step progress indication.
## Example Workflow
1. Add the **CogView4 Generator** node to your workspace
2. Configure the prompt and other desired parameters
3. Connect the output of the CogView4 Generator to a Preview Image node to view the result
4. Optionally, connect to a Save Image node to save the image to disk
## Performance Optimization
- Model CPU offload: loads parts of the model to CPU when not in use
- VAE slicing: processes the image in smaller slices
- VAE tiling: divides the image into blocks for processing
## Troubleshooting
### Import Error
If you encounter import errors like `No module named 'diffusers'`, make sure you have installed all required dependencies.
### CUDA Memory Errors
If you receive errors like `CUDA out of memory`, try:
- Close other applications using the GPU
- Decrease the image size parameters
- Enable the CPU offload function (enabled by default)
### Slow First Run
On the first run, the model will be downloaded from Hugging Face (approximately 12GB). This can take some time depending on your internet connection.