DATASET_README.md

metadata

title: LEMM Training Data & LoRA Storage
tags:
  - music-generation
  - audio
  - lora
  - training-data
  - diffrhythm2
license: mit

LEMM Dataset Storage

This dataset repository stores training data and LoRA adapters for LEMM (Let Everyone Make Music) - an advanced AI music generation system.

🎯 Purpose

This repository serves as persistent storage for:

• LoRA Adapters: Fine-tuned music generation models
• Prepared Datasets: Training data extracted from various music datasets
• Cross-rebuild Persistence: Data survives HuggingFace Space rebuilds

📁 Repository Structure

lemm-dataset/
├── loras/                    # LoRA adapter storage
│   ├── {lora_name}/         # Each LoRA in its own folder
│   │   ├── final_model.pt   # Trained LoRA weights
│   │   └── config.yaml      # Training configuration
│   └── ...
│
└── datasets/                 # Prepared training datasets
    ├── {dataset_key}/       # Each dataset in its own folder
    │   ├── train/           # Training samples
    │   ├── val/             # Validation samples
    │   └── metadata.json    # Dataset metadata
    └── ...

🔄 Automatic Sync

The LEMM Space automatically:

• Downloads all LoRAs and datasets on startup
• Uploads newly trained LoRAs after training completes
• Uploads newly prepared datasets after preparation

🔐 Access Control

• Visibility: Public (anyone can view)
• Access Requests: Enabled with automatic approval
• Purpose: Allows LEMM Space to read/write data

🚀 Usage

From LEMM Space

Data syncs automatically - no manual intervention needed.

From Your Own Code

from huggingface_hub import hf_hub_download, snapshot_download

# Download a specific LoRA
lora_path = snapshot_download(
    repo_id="Gamahea/lemm-dataset",
    repo_type="dataset",
    allow_patterns="loras/your_lora_name/*"
)

# Download all datasets
datasets_path = snapshot_download(
    repo_id="Gamahea/lemm-dataset",
    repo_type="dataset",
    allow_patterns="datasets/*"
)

📊 Supported Datasets

LEMM can prepare and train on:

• GTZAN: Music genre classification dataset
• MusicCaps: Google's music captioning dataset
• Free Music Archive (FMA): Large-scale music dataset
• Custom datasets: Upload your own music collections

🎵 LoRA Training

LoRA (Low-Rank Adaptation) allows efficient fine-tuning of DiffRhythm2 for:

• Specific music styles
• Genre specialization
• Artist emulation
• Custom sound aesthetics

🛠️ Related Projects

• LEMM Space: Gamahea/lemm-test-100
• DiffRhythm2: Advanced music generation with built-in vocals

📝 License

MIT License - Feel free to use and modify

🤝 Contributing

This is a storage repository. To contribute to LEMM:

1. Visit the LEMM Space
2. Train your own LoRAs
3. Share your results with the community

⚠️ Notes

• Data is organized for LEMM's automatic sync system
• Manual edits may be overwritten by Space operations
• Each LoRA/dataset includes configuration metadata
• Storage persists across Space rebuilds