Extensions/FL HeartMuLa
ComfyUI Extension

FL HeartMuLa

FL HeartMuLa - Multilingual AI music generation nodes for ComfyUI. Generate full songs with lyrics using the HeartMuLa model family. Supports English, Chinese, Japanese, Korean, and Spanish with song structure control via section markers and style tags.

By filliptm·Created 7 months ago·Updated 4 months ago· 129
filliptm/ComfyUI_FL-HeartMuLa
Nodes6
On cloudLocal install
CategoryFL HeartMuLa, 🎵FL HeartMuLa
Stars129
Updated4 months ago
Readme

FL HeartMuLa

Multilingual AI music generation nodes for ComfyUI powered by the HeartMuLa model family. Generate full songs with lyrics in English, Chinese, Japanese, Korean, and Spanish.

HeartMuLa Patreon

Workflow Preview

Features

  • Multilingual Lyrics - Generate music with vocals in English, Chinese, Japanese, Korean, and Spanish
  • Song Structure Control - Use section markers like [Verse], [Chorus], [Bridge] to define song structure
  • Style Tags - Control genre, vocal type, mood, tempo, and instruments
  • 4-Minute Songs - Generate up to 240 seconds of continuous audio
  • Zero-Shot Generation - No fine-tuning required, just provide lyrics and tags
  • Modular Pipeline - Separate nodes for conditioning, sampling, and decoding

Nodes

| Node | Description | |------|-------------| | Model Loader | Downloads and caches HeartMuLa models | | Conditioning | Tokenize lyrics and tags into model conditioning | | Sampler | Generate audio tokens with CFG and temperature control | | Decode | Convert audio tokens to waveform using HeartCodec | | Tags Builder | Build style tags with genre, vocal, mood selection | | Transcribe | Extract lyrics from existing audio |

Installation

ComfyUI Manager

Search for "FL HeartMuLa" and install.

Manual

cd ComfyUI/custom_nodes
git clone https://github.com/filliptm/ComfyUI_FL-HeartMuLa.git
cd ComfyUI_FL-HeartMuLa
pip install -r requirements.txt

Quick Start

  1. Add FL HeartMuLa Model Loader and select 3B model
  2. Connect to FL HeartMuLa Conditioning node
  3. Enter lyrics with section markers:
    [Verse]
    Walking down the empty street
    Thinking about you and me
    
    [Chorus]
    We belong together
    Now and forever
    
  4. Add style tags: pop, female vocal, energetic
  5. Connect to SamplerDecodePreview Audio

Section Markers

HeartMuLa supports these official section markers:

| Marker | Usage | |--------|-------| | [Intro] | Opening instrumental or vocal intro | | [Verse] | Main verses | | [Prechorus] | Build-up before chorus | | [Chorus] | Main hook/chorus | | [Bridge] | Contrasting section | | [Outro] | Ending section | | [Instrumental] | Non-vocal sections |

Style Tags

Combine tags to control the output style:

  • Genre: pop, rock, electronic, jazz, classical, hip-hop, r&b, country, folk, metal, indie
  • Vocal: female vocal, male vocal, duet, choir, instrumental
  • Mood: energetic, melancholic, uplifting, calm, aggressive, romantic, dreamy, dark
  • Tempo: slow, medium, fast
  • Instruments: piano, guitar, drums, synth, strings, etc.

Example: indie rock, male vocal, melancholic, slow, acoustic guitar

Models

| Model | Size | VRAM (fp16) | VRAM (4-bit) | Notes | |-------|------|-------------|--------------|-------| | 3B | ~6GB | ~12GB | ~6GB | Released, recommended | | 7B | ~14GB | ~24GB | ~12GB | Coming soon |

Models download automatically on first use to ComfyUI/models/heartmula/.

Memory Modes

The Model Loader includes a memory_mode option to optimize for different VRAM configurations:

| Mode | Description | Use Case | |------|-------------|----------| | auto | Auto-detect based on available VRAM | Recommended default | | normal | Full speed, no memory optimizations | 16GB+ VRAM | | low | Moderate memory savings | 10-16GB VRAM | | ultra | Aggressive memory cleanup | 8-10GB VRAM |

Requirements

  • Python 3.10+
  • 16GB RAM minimum (32GB+ recommended)

Supported Platforms

| Platform | Device | Notes | |----------|--------|-------| | NVIDIA GPU | CUDA | 12GB+ VRAM (or 6GB with 4-bit quantization) | | Apple Silicon | MPS | M1/M2/M3/M4 Macs supported | | CPU | CPU | Slow fallback option |

Platform Notes

  • NVIDIA: CUDA 12.1+ recommended. 4-bit quantization available via bitsandbytes
  • Apple Silicon: Uses Metal Performance Shaders (MPS). 4-bit quantization not available (CUDA only)
  • CPU: Works but very slow, not recommended for generation

Parameters

Sampler Settings

| Parameter | Default | Range | Description | |-----------|---------|-------|-------------| | max_duration_sec | 60 | 10-240 | Maximum audio length | | temperature | 1.0 | 0.1-2.0 | Sampling randomness | | top_k | 50 | 1-500 | Top-k token filtering | | cfg_scale | 1.5 | 1.0-10.0 | Classifier-free guidance | | seed | -1 | -1 to 2^31 | Random seed (-1 = random) |

Credits

License

Apache 2.0