ComfyUI-nunchaku - AI Vision Tools Tool

Overview

ComfyUI-nunchaku is a ComfyUI plugin that integrates Nunchaku, an efficient inference engine for 4-bit neural networks quantized with SVDQuant, into the ComfyUI workflow. It provides performance-focused features including multi-LoRA, ControlNet support, FP16 attention, and compatibility with modern GPUs.

Key Features

• Integrates the Nunchaku inference engine into ComfyUI workflows.
• Optimized for 4-bit neural networks quantized with SVDQuant.
• Supports multi-LoRA for combined fine-tuning layers.
• ControlNet node compatibility within ComfyUI.
• FP16 attention support for reduced-precision compute.
• Designed for compatibility with modern GPUs.

Ideal Use Cases

• Accelerate inference of 4-bit SVDQuant-quantized models.
• Experiment with combined multi-LoRA weight merges.
• Integrate ControlNet-conditioned pipelines in ComfyUI.
• Run efficient model inference on modern GPUs.

Getting Started

• Install ComfyUI.
• Download ComfyUI-nunchaku from the GitHub repository.
• Follow the repository installation instructions to add the plugin.
• Load a 4-bit SVDQuant-quantized model into ComfyUI.
• Enable the Nunchaku engine within your ComfyUI workflow.
• Configure multi-LoRA and ControlNet nodes as needed.
• Enable FP16 attention if supported by your GPU.

Pricing

Not disclosed in the project description or repository.

Limitations

• Requires ComfyUI as the host environment.
• Primarily tailored for 4-bit SVDQuant-quantized models.
• Best performance depends on modern GPU support for FP16.

Key Information

• Category: Vision Tools
• Type: AI Vision Tools Tool