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Music generation using a Long Short-Term Memory (LSTM) neural network. The gennhausser project uses TensorFlow and music21 libraries to create a synthetic dataset, train an LSTM model, and generate music sequences.

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Twitter: @NorowaretaGemu License: MIT



Python
TensorFlow Flask


The gennhausser project is for music generation using a Long Short-Term Memory (LSTM) neural network. The gennhausser project uses TensorFlow and music21 libraries to create a synthetic dataset, train an LSTM model, and generate MIDI sequences.


## Scripts:
  • main.py: The selection menu for gennhuasser
  • app.py: Run gennhuasser as a web-server

/scripts/

  • trainer.py: Runs gennhuasser trainer
  • install_dependencies.py: Install dependencies

How to Run:

Install Requirements

Using Python directly:

pip install -r requirements.txt

Or run:

  • install_requirements.bat


Run main.py

Using Python directly:

python main.py

Using provided scripts:

Windows:

  • .\run.bat or
  • .\run.ps1

Unix-like systems (Linux/macOS):

  • .\run.sh



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Music generation using a Long Short-Term Memory (LSTM) neural network. The gennhausser project uses TensorFlow and music21 libraries to create a synthetic dataset, train an LSTM model, and generate music sequences.

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