heartmula

Generate complete songs locally from lyrics and tags using HeartMuLa.

Updated Jun 1, 2026
One-click install
npx skills add https://github.com/SatangThevalue/ai-skills --skill heartmula-satangthevalue
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: heartmula
Source: https://github.com/SatangThevalue/ai-skills/tree/main/skills/media/heartmula
Command: npx skills add https://github.com/SatangThevalue/ai-skills --skill heartmula-satangthevalue

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

HeartMuLa provides an open-source, local workflow to generate full songs conditioned on lyrics and descriptive tags, enabling offline music creation without relying on proprietary tools.

Core Features & Use Cases

  • HeartMuLa: a music language model (3B/7B) for generation from lyrics + tags
  • HeartCodec: a 12.5Hz codec for high-fidelity audio reconstruction
  • HeartTranscriptor: Whisper-based lyrics transcription
  • HeartCLAP: audio-text alignment for synchronization
  • Local, offline operation with hardware guidelines and installation steps for reproducible experiments
  • Use cases include solo music production, research explorations, and educational demos on AI-driven music

Quick Start

Provide lyrics and tags and run HeartMuLa to generate a complete song on a local machine.

Frequently Asked Questions about heartmula

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate music from lyrics offline using open-source AI?

Generate music from lyrics offline by inputting text lyrics and descriptive tags into a local music language model. This process uses multi-model orchestration to synthesize and reconstruct high-fidelity audio without relying on proprietary cloud tools.

Can I run Suno-style AI music generation locally on my own machine?

Yes, you can run Suno-style AI music generation locally by orchestrating a 3B or 7B music language model with a 12.5Hz audio codec. This offline setup enables reproducible experiments and solo music production directly on your hardware.

What do I need to set up an offline AI music generation workflow?

Offline AI music generation requires local hardware meeting specific guidelines and a multi-model stack including a music language model, audio codec, Whisper-based transcription, and audio-text alignment components to ensure accurate synchronization.

How does audio-text alignment synchronize generated music with lyrics?

Audio-text alignment synchronizes generated music with lyrics by mapping the audio output to the text inputs. This ensures the reconstructed high-fidelity audio matches the timing and structure of the original lyrical prompts.

Are there limitations to using open-source models for local music generation?

Open-source local music generation demands substantial hardware resources to operate a multi-model orchestration stack. Users must manage installation and configuration manually, making it more suited for research, educational demos, and solo production rather than rapid commercial scaling.