Musique IA
midi-mcp-server
MCP server for AI-generated MIDI — text in, compositions out.
★ 54 étoilesMIT
Voir le guide →Tegridy-MIDI-Dataset est un projet de musique IA open source, créé par asigalov61 (asigalov61/Tegridy-MIDI-Dataset sur GitHub). Il compte 296 étoiles sur GitHub et 21 forks, il est publié sous la licence Apache-2.0 et a été mis à jour pour la dernière fois sur GitHub le 21 septembre 2026.
A curated MIDI dataset built for training precise music AI models.
Check the README for what the dataset contains and its structure.
Grab the MIDI files or clone the full repository.
Use the included converters and parsers to format MIDI for training.
Feed the prepared data into your music AI training pipeline.
A dataset assembled specifically for music AI work.
Multi-track MIDIs for richer model training.
Tools to convert MIDI formats for your pipeline.
Parse and inspect MIDI files in Python.
Includes karaoke-style MIDI content.
Designed for composition and generation models.
Download the dataset and its tools.
git clone https://github.com/asigalov61/Tegridy-MIDI-Dataset.git
cd Tegridy-MIDI-DatasetSet up the environment for the MIDI utilities.
pip install -r requirements.txtList the MIDI files and try the parser tools.
ls | head -20A curated MIDI dataset for creating precise music AI models, maintained at asigalov61/Tegridy-MIDI-Dataset.
Yes. It is Apache-2.0 licensed.
MIDI files, including multi-track and karaoke-style content, plus conversion tools.
No. It is data plus Python utilities; training models is the compute-heavy part.
Researchers and builders training music composition or generation models.
MCP server for AI-generated MIDI — text in, compositions out.
Agent skill that turns text descriptions into real MIDI compositions.
Research code for instruction-based text-to-music editing of music models.
Local AI music studio: ACE-Step plus YuE2, stems, MIDI, and a built-in DAW.
Compose multi-track MIDI with Gemini and DeepSeek.
An audio quality metric and loss for training cleaner models.
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