754,000+ skills indexed

ChensihaknirothCOMMUNITY

Explore all skills by this author →

Verified:GitHub

heartmula

Generate full songs from lyrics and style tags using HeartMuLa open-source music models.

Updated Jun 7, 2026

Search Tags:#audio #music generation #heartmula #gpu inference #lyrics to music #open-source suno #ai songs

One-click install

npx skills add https://github.com/Chensihakniroth/ANAKOT-AGENT --skill heartmula-chensihakniroth

Or copy as Structured Prompt for Agent▼

Please help me install this Agent Skill.
Skill: heartmula
Source: https://github.com/Chensihakniroth/ANAKOT-AGENT/tree/main/skills/media/heartmula
Command: npx skills add https://github.com/Chensihakniroth/ANAKOT-AGENT --skill heartmula-chensihakniroth

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Generating complete songs with vocals from text typically requires paid services like Suno. This Skill lets you run the open-source HeartMuLa music foundation models locally to produce full MP3 songs from lyrics and style tags, with multilingual support and offline capability. ## Core Features & Use Cases - Lyrics-to-Song Generation: Produce complete songs (up to 4 minutes, 48kHz stereo MP3) from bracketed lyrics and comma-separated style tags using the 3B or 7B HeartMuLa models. - Local GPU Inference: Run entirely offline on an NVIDIA GPU with as little as 8GB VRAM using lazy loading, or split models across multiple GPUs. - Dependency & Patch Guidance: Includes required fixes for transformers 5.x compatibility, RoPE cache initialization, and HeartCodec checkpoint loading. - Use Case: A content creator writes lyrics in a text file with [Verse]/[Chorus] tags, specifies tags like "piano,happy,wedding", and generates a finished MP3 song locally in about 4 minutes. ## Quick Start Generate a song from my lyrics file and the tags "rock,energetic,guitar" using the HeartMuLa 3B model and save it as an MP3.

Frequently Asked Questions about heartmula

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

FAQPage Schema

How do I generate a song from lyrics with HeartMuLa?▼

Clone the heartlib repository, install it in a Python 3.10 virtual environment, download the HeartMuLa and HeartCodec checkpoints, then run examples/run_music_generation.py with your lyrics file, tags file, and output path. A 4-minute song takes roughly 4 minutes on GPU.

What is a good open-source Suno alternative for local music generation?▼

HeartMuLa is an Apache-2.0 family of music foundation models that generates full songs from lyrics and tags, comparable to Suno. It includes a 3B/7B music language model, the HeartCodec audio codec, and multilingual support, all runnable locally.

How much VRAM does HeartMuLa need to run?▼

HeartMuLa requires a minimum of 8GB VRAM with lazy loading enabled, which peaks around 6.2GB for the 3B model. 16GB or more is recommended, and multi-GPU setups can split the language model and codec across devices.

Can HeartMuLa run on CPU or without an NVIDIA GPU?▼

Yes, CPU mode works via --mula_device cpu --codec_device cpu, but generation is extremely slow (30-60+ minutes per song) and needs 12GB+ free RAM. Without a GPU, a cloud GPU service or the online demo is recommended.

Why does HeartMuLa fail after installing with newer transformers?▼

The pinned dependencies conflict with newer packages, and transformers 5.x breaks RoPE cache initialization and HeartCodec checkpoint loading. You must upgrade datasets and transformers, then apply the two source patches documented in the Skill instructions.

What are the limitations of HeartMuLa music generation?▼

Style tags may be ignored since lyrics tend to dominate conditioning, Triton GPU acceleration is unavailable on macOS, and RTX 5080 incompatibility has been reported. HeartCodec should also stay in fp32, as bf16 degrades audio quality.

Related Skills

Explore More Design & Creative Skills→

heartmula

Generates full songs from lyrics and style tags using HeartMuLa open-source music models.

KaiserWhoLearns

FFmpeg Audio Processing

Extract, normalize, and mix audio from video files using FFmpeg commands.

music-lyrics

Extract timestamped lyrics from audio using faster-whisper.

ai-music-generation

Generates music and songs with AudioCraft and HeartMuLa, and analyzes audio via spectrograms.