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2024-08-15 06:41:47 +02:00
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@@ -12,17 +12,25 @@ While quantization wasn't feasible for regular UNET models (conv2d), transformer
> [!IMPORTANT]
> Make sure your ComfyUI is on a recent-enough version to support custom ops when loading the UNET-only.
To install the custom node, clone it to your custom_nodes ComfyUI folder using the following command:
To install the custom node normally, git clone this repository and install the only dependency for inference (`pip install --upgrade gguf`)
```
git clone https://github.com/city96/ComfyUI-GGUF
```
To install the custom node on standalone, open a CMD inside the "ComfyUI_windows_portable" folder (where your `run_nvidia_gpu.bat` file is) and use the following commands:
```
git clone https://github.com/city96/ComfyUI-GGUF ComfyUI/custom_nodes/ComfyUI-GGUF
```
To install the required `gguf` python package on the standalone ComfyUI, Open a CMD where your `run_nvidia_gpu.bat` file is and use the following command:
```
.\python_embeded\python.exe -s -m pip install -r .\ComfyUI\custom_nodes\ComfyUI-GGUF\requirements.txt
```
## Usage
Simply use the GGUF Unet loader found under the `bootleg` category. You can find [pre-quantized models for flux1-dev here](https://huggingface.co/city96/FLUX.1-dev-gguf) - place these in your `ComfyUI/models/unet` folder.
Simply use the GGUF Unet loader found under the `bootleg` category. Place the .gguf model files in your `ComfyUI/models/unet` folder.
Pre-quantized models:
- [flux1-dev GGUF](https://huggingface.co/city96/FLUX.1-dev-gguf)
- [flux1-schnell GGUF](https://huggingface.co/city96/FLUX.1-schnell-gguf)