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.
How much VRAM does FL HeartMuLa require?
Direct Answer: The ComfyUI node FL HeartMuLa requires a minimum base VRAM of 1536MB and is optimized for GPUs with at least 6GB of VRAM. Low VRAM mode is fully supported for resource-constrained setups.
- Base VRAM:
- 1536MB (1.5GB)
- Recommended GPU:
- 6GB+ VRAM
- Low VRAM Mode:
- ✓ Supported
- Estimation Confidence:
- MEDIUM
Interactive VRAM Compatibility Estimator
Your GPU has plenty of headroom. You can run this node safely with your active configurations!
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Deploy on Cloud GPUs
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What Python packages are required for FL HeartMuLa?
Direct Answer: Running FL HeartMuLa requires installing the following Python package dependencies: accelerate>=1.0.0, bitsandbytes>=0.42.0, einops>=0.8.0, huggingface_hub>=0.20.0, modelscope>=1.20.0, numpy, soundfile, tokenizers>=0.20.0, torch>=2.4.0, torchao>=0.9.0, torchaudio>=2.4.0, torchtune>=0.4.0, torchvision>=0.19.0, tqdm, transformers>=4.45.0, vector-quantize-pytorch>=1.20.0. This node specifically requires PyTorch version 2.4.0 or newer.
accelerate>=1.0.0
bitsandbytes>=0.42.0
einops>=0.8.0
huggingface_hub>=0.20.0
modelscope>=1.20.0
numpy
soundfile
tokenizers>=0.20.0
torch>=2.4.0
torchao>=0.9.0
torchaudio>=2.4.0
torchtune>=0.4.0
torchvision>=0.19.0
tqdm
transformers>=4.45.0
vector-quantize-pytorch>=1.20.0Interactive Setup & Dependency Resolver
# Loading command...Special Environment Requirements:
Requires PyTorch version 2.4.0+.
# Loading PyTorch command...Frequently Asked Questions
How much VRAM does FL HeartMuLa require?
FL HeartMuLa requires a minimum of 1536MB (1.5GB) of VRAM for base operation. For optimal performance, a GPU with at least 6GB of VRAM is recommended. This node supports low VRAM mode for resource-constrained setups.
Can I run FL HeartMuLa on an RTX 3060, RTX 4070, or RTX 4090?
✅ RTX 3060 (12GB): Yes, fully compatible with 9.3GB headroom. ✅ RTX 4070 (12GB): Yes, fully compatible with 9.3GB headroom. ✅ RTX 4070 Ti (16GB): Yes, fully compatible with 12.9GB headroom. ✅ RTX 4090 (24GB): Yes, fully compatible with 20.1GB headroom
What PyTorch version does FL HeartMuLa need?
FL HeartMuLa requires the following PyTorch-related packages: torch>=2.4.0, torchao>=0.9.0, torchaudio>=2.4.0, torchtune>=0.4.0, torchvision>=0.19.0, vector-quantize-pytorch>=1.20.0. Ensure your ComfyUI environment has these installed. Ensure your PyTorch installation matches your CUDA version (use torch.version.cuda to check).
What Python packages are required for FL HeartMuLa?
To run FL HeartMuLa, you need to install: accelerate>=1.0.0, bitsandbytes>=0.42.0, einops>=0.8.0, huggingface_hub>=0.20.0, modelscope>=1.20.0, numpy, soundfile, tokenizers>=0.20.0, torch>=2.4.0, torchao>=0.9.0, torchaudio>=2.4.0, torchtune>=0.4.0, torchvision>=0.19.0, tqdm, transformers>=4.45.0, vector-quantize-pytorch>=1.20.0. You can install these using pip or add them to your requirements.txt file.
How can I reduce VRAM usage when running FL HeartMuLa?
FL HeartMuLa supports low VRAM mode. To reduce memory usage: (1) Enable --lowvram or --medvram flags in ComfyUI, (2) Reduce batch size to 1, (3) Use fp16 or fp8 precision if supported, (4) Close other GPU applications.
How do I install FL HeartMuLa in ComfyUI?
To install FL HeartMuLa: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/filliptm/ComfyUI_FL-HeartMuLa, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.