kijai/ComfyUI-KwaiKolorsWrapper

Diffusers wrapper to run Kwai-Kolors model

593

stars

42

commits

Python

primary language

Oct 18, 2024

updated

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:

image

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

goes into:

ComfyUI\models\LLM\checkpoints image

image

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:

ModelSize
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.

image

image

Contributors

kijai

39 commits

comfy-pr-bot

2 commits

githubcto

1 commits

kijai/ComfyUI-KwaiKolorsWrapper

Diffusers wrapper to run Kwai-Kolors model

593

stars

42

commits

Python

primary language

Oct 18, 2024

updated

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:

image

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

goes into:

ComfyUI\models\LLM\checkpoints image

image

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:

ModelSize
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.

image

image

Contributors

kijai

39 commits

comfy-pr-bot

2 commits

githubcto

1 commits

Languages

Python

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