From 4750e4562393f9e8e2d8bc3f4778167c609e9bea Mon Sep 17 00:00:00 2001 From: City <125218114+city96@users.noreply.github.com> Date: Thu, 15 Aug 2024 06:21:19 +0200 Subject: [PATCH] Update README.md --- README.md | 23 +++++++++++++++++++++++ 1 file changed, 23 insertions(+) diff --git a/README.md b/README.md index ecc7a68..4b15e46 100644 --- a/README.md +++ b/README.md @@ -1,2 +1,25 @@ # ComfyUI-GGUF GGUF Quantization support for native ComfyUI models + +This is currently very much WIP. These custom nodes provide support for model files stored in the GGUF format popularized by [llama.cpp](https://github.com/ggerganov/llama.cpp). + +While quantization wasn't feasible for regular UNET models (conv2d), transformer/DiT models such as flux seem less affected by quantization. This allows running it in much lower bits per weight variable bitrate quants on low-end GPUs. + +![Comfy_Flux1_dev_Q4_0_GGUF_1024](https://github.com/user-attachments/assets/23150750-bcb6-49ef-a78f-9c814528a640) + +## Installation + +To install the custom node, clone it to your custom_nodes ComfyUI folder using the following command: + +``` +git clone https://github.com/city96/ComfyUI-GGUF custom_nodes/ComfyUI-GGUF +``` + +To install the required `gguf` python package on the standalone ComfyUI, use the following: +``` +.\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.