ACE-Step 1.5 is an advanced open-source foundation model for AI-driven music generation that pushes beyond traditional limitations in speed, musical coherence, and controllability by innovating in architecture and training design. It integrates cutting-edge generative techniques—such as diffusion-based synthesis combined with compressed autoencoders and lightweight transformer elements—to produce high-quality full-length music tracks with rapid inference times, capable of generating a complete song in seconds on modern GPUs while remaining efficient enough to run on consumer-grade hardware with minimal memory requirements. Beyond straightforward text-to-music synthesis, ACE-Step 1.5 enables flexible creative workflows, including tasks like cover generation, editing existing tracks, transforming vocals to background accompaniment, and stylistic personalization using low-rank adaptation from just a few example songs.

Features

  • Fast full-song generation (seconds per track) with low VRAM requirements
  • Diffusion-plus-transformer architecture for musical coherence
  • Multilingual prompt support (50+ languages)
  • Flexible editing (repainting, remixing, vocal/BGM conversion)
  • Personalization via lightweight LoRA training
  • Extensible workflows and integration with UI tools

Project Samples

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License

MIT License

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ACE-Step 1.5 Web Site

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Additional Project Details

Operating Systems

Linux, Mac, Windows

Programming Language

Python

Related Categories

Python AI Music Generators, Python AI Models

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