🎨 Diffusers in ComfyUI

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

Why? ComfyUI's built-in nodes are limited to specific model architectures. This plugin lets you use any HuggingFace Diffusers pipeline — including new models the day they're released — with full ControlNet, LoRA, and B-LoRA support.

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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

1. Launch ComfyUI
2. Open ComfyUI Manager
3. Search for "Diffusers in Comfy UI"
4. 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:

1. Place your B-LoRA file in ComfyUI/lora/ folder
2. In the BLoRA node, specify filename (e.g., vangogh.safetensors)
3. 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 — check the issues page or submit PRs.

License

MIT