← Open Source
kijai

ComfyUI-KwaiKolorsWrapper

Diffusers wrapper to run Kwai-Kolors model.

AI EngineeringBuild agent workflow (visual)Python
Open on GitHub
Momentum
+0stars in 24 hours0.0%
593
Stars
35
Forks
+1
This week
3
Contributors
Created 2024-07-06 · Updated 2026-10-14 · #16329 today
Top developers
kijaigithubcto
README

ComfyUI wrapper for Kwai-Kolors

Rudimentary wrapper that runs Kwai-Kolors text2image pipeline using diffusers.

Update - safetensors

Added alternative way to load the ChatGLM3 model from single safetensors file (the configs are included in this repo already). Including already quantized models:

https://huggingface.co/Kijai/ChatGLM3-safetensors/upload/main

goes into:

ComfyUI\models\LLM\checkpoints

Installation:

Clone this repository to 'ComfyUI/custom_nodes` folder.

Install the dependencies in requirements.txt, transformers version 4.38.0 minimum is required:

pip install -r requirements.txt

or if you use portable (run this in ComfyUI_windows_portable -folder):

python_embeded\python.exe -m pip install -r ComfyUI\custom_nodes\ComfyUI-KwaiKolorsWrapper\requirements.txt

Models (fp16, 16.5GB) are automatically downloaded from https://huggingface.co/Kwai-Kolors/Kolors/tree/main

to ComfyUI/models/diffusers/Kolors

Model folder structure needs to be the following:

PS C:\ComfyUI_windows_portable\ComfyUI\models\diffusers\Kolors> tree /F
│   model_index.json
│
├───scheduler
│       scheduler_config.json
│
├───text_encoder
│       config.json
│       pytorch_model-00001-of-00007.bin
│       pytorch_model-00002-of-00007.bin
│       pytorch_model-00003-of-00007.bin
│       pytorch_model-00004-of-00007.bin
│       pytorch_model-00005-of-00007.bin
│       pytorch_model-00006-of-00007.bin
│       pytorch_model-00007-of-00007.bin
│       pytorch_model.bin.index.json
│       tokenizer.model
│       tokenizer_config.json
│       vocab.txt
│
└───unet
        config.json
        diffusion_pytorch_model.fp16.safetensors

To run this, the text enconder is what takes most of the VRAM, but can be quantized to fit approximately these amounts:

Model Size
fp16 ~13 GB
quant8 ~8 GB
quant4 ~4 GB

After that, the sampling single image at 1024 can be expected to take similar amounts than SDXL. For VAE the base SDXL VAE is used.

Nearby in the ranking
Similar items