🎨 Diffusers in ComfyUI

Bring the full power of Hugging Face Diffusers pipelines directly into ComfyUI

[](https://github.com/ltdrdata/ComfyUI-Manager)

[](https://registry.comfy.org/)

[](https://github.com/maepopi/Diffusers-in-ComfyUI/stargazers)

[](https://opensource.org/licenses/MIT)

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✨ Features

🔥 Full Diffusers Pipeline Integration – Text2Img, Img2Img, and Inpainting pipelines

🎯 SDXL Support – Works with both SD 1.5 and SDXL models

🎨 ControlNet Compatible – Seamless ControlNet integration with any Hugging Face model

🧩 LoRA & B-LoRA Support – Load LoRAs and advanced B-LoRAs for style/content separation

⚡ Low VRAM Mode – Optimized for limited GPU memory with CPU offloading

🛠️ Modular Design – Clean, reusable nodes for flexible workflows

📦 Easy Installation – Available via ComfyUI Manager and Comfy Registry

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🚀 Quick Start

Option 1: Install via Comfy Registry (Recommended)

comfy node registry-install diffusers-in-comfyui

Option 2: Install via ComfyUI Manager

Launch ComfyUI

Open ComfyUI Manager

Search for “Diffusers in Comfy UI”

Click Install

Option 3: Manual Installation

cd ComfyUI/custom_nodes/
git clone https://github.com/maepopi/Diffusers-in-ComfyUI.git
cd Diffusers-in-ComfyUI
pip install -r requirements.txt

After installation, you’ll find the nodes under “Diffusers-in-Comfy” in your node menu! 🎉

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📖 Usage

Available Node Categories

🔧 Pipeline Nodes (Diffusers-in-Comfy/Pipelines)

Set up your generation pipeline with these nodes:

Text2ImgStableDiffusionPipeline – Generate images from text prompts

Img2ImgStableDiffusionPipeline – Transform existing images

InpaintingStableDiffusionPipeline – Fill masked regions

Pipeline Configuration Options:

✅ SDXL support toggle

🎨 Custom VAE (e.g., "stabilityai/sd-vae-ft-mse")

🕹️ ControlNet integration (e.g., "XLabs-AI/flux-controlnet-canny")

💾 Low VRAM mode for memory-constrained GPUs

🎯 Inference Nodes (Diffusers-in-Comfy/Inference)

Execute your generation with fine-tuned control:

GenerateTxt2Image – Text-to-image generation

GenerateImg2Image – Image-to-image transformation

GenerateInpaintImage – Inpainting with masks

Common Parameters:

Seed, Positive/Negative prompts

Inference steps, Width/Height

Guidance scale

ControlNet image & scale

🛠️ Utils Nodes (Diffusers-in-Comfy/Utils)

Image preprocessing utilities:

Make Canny – Convert images to Canny edge maps for ControlNet

Outputs: Processed image + Preview

🧩 Component Nodes (Diffusers-in-Comfy/Components)

Extend your pipelines with adapters:

LoraLoader – Load LoRA adapters with custom weights

BLoRA – Advanced style/content separation (SDXL only)

⚠️ Note: B-LoRA works with ControlNet but not with standard LoRAs

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📸 Workflow Examples

Text-to-Image (SD 1.5)

Inpainting (SDXL)

Image-to-Image (SD 1.5)

LoRA Integration

B-LoRA Style Transfer (SDXL)

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🎯 Advanced: B-LoRA Usage

B-LoRA enables powerful style and content separation. Original paper

Setup:

Place your B-LoRA file in ComfyUI/lora/ folder

In the BLoRA node, specify filename (e.g., vangogh.safetensors)

Ensure SDXL pipeline is loaded with is_sdxl=True

Important Notes:

✅ Compatible with ControlNet

❌ Cannot be combined with standard LoRAs

🎨 SDXL models only

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🗺️ Roadmap

[ ] IPAdapter support

[ ] Automatic model architecture detection via ComfyAPI

[ ] Local & remote model loading with URL support

[ ] File browser for image selection (no manual paths)

[ ] Auto-strip quotes from input paths

[ ] Auto-detect B-LoRAs in lora folder

[ ] More research paper implementations 🔬

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🙏 Acknowledgments

This project was inspired by ComfyUI-Diffusers. Special thanks to:

Comfy Registry team for platform inclusion

ltdrdata for ComfyUI Manager integration

The ComfyUI community for continuous feedback

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🤝 Contributing

Contributions, issues, and feature requests are welcome!

Feel free to check the issues page or submit PRs.

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📝 License

This project is MIT licensed.

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💬 Contact & Support

🐛 Report a bug

💡 Request a feature

⭐ Star this repo if you find it useful!

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