Ace-Step 1.5 prompt tips: how I get more controllable music output (github.com)

ACE-Step 1.5 has been announced as a revolutionary open-source music foundation model that enables high-quality, commercial-grade music generation on consumer-grade hardware. With impressive speed—under 2 seconds for a full song on an A100 GPU and less than 10 seconds on an RTX 3090—this model can operate with less than 4GB of VRAM. It incorporates a hybrid architecture where a Language Model (LM) acts as an omnipotent planner, enabling users to generate everything from brief loops to extensive 10-minute tracks. Intriguingly, its internal reinforcement learning mechanism eliminates the common biases found in external reward systems, aligning the creation process with user prompts more naturally across 50+ languages. The significance of ACE-Step 1.5 lies in its unique features, which blend stylistic control with powerful editing tools, enhancing creativity for musicians, producers, and content creators. Users can perform tasks such as cover generation, track separation, and even vocal-to-background music conversion. The model supports training a lightweight LoRA with just a handful of songs, allowing for high levels of personalization. As an accessible tool for generating original music across various genres, ACE-Step could transform creative workflows and inspire innovative applications in the realms of music education and entertainment, while also highlighting the importance of responsible use to prevent potential copyright issues.