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EasyControl

Implementation of EasyControl provides efficient and flexible control for Diffusion Transformer models.

Introduction

EasyControl

EasyControl is an implementation focused on adding efficient and flexible control for Diffusion Transformer models. It proposes a unified conditional framework designed to enhance compatibility and generation flexibility while maintaining efficiency.

Key Features:
  • Unified Conditional Framework: EasyControl integrates various conditioning methods for improved model interaction.
  • High Compatibility: Supports a plug-and-play structure simplifying the integration of different control techniques.
  • Versatile Use Cases: Allows single and multi-condition control, enabling diverse image generation scenarios.
  • Easy Integration: Lightweight Condition Injection LoRA module for rapid model adaptation.
  • Enhanced Efficiency: Combines Causal Attention mechanisms with KV Cache technology to speed up inference.
Benefits:
  • Flexibility: Users can generate images across multiple resolutions and aspect ratios.
  • User-Friendly Implementation: The provided API and comprehensive guides make it easy for users to get started with their own models.
  • Research and Commercial Use: Released under the Apache License, supporting both academic research and commercial applications.
Highlights:
  • Integrated with CFG-Zero to boost image fidelity.
  • Ghibli-style portrait generation capabilities.
  • Released pre-trained models for immediate use and experimentation.

Information

  • Publisher
    AISecKit
  • Websitegithub.com
  • Published date2025/04/28

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