VampNet

This repository contains recipes for training generative music models on top of the Lyrebird Audio Codec.

Setting up

Install LAC

install AudioTools

git clone https://github.com/hugofloresgarcia/audiotools.git
pip install -e ./audiotools

install the LAC library.

git clone https://github.com/hugofloresgarcia/lac.git
pip install -e ./lac

install VampNet

git clone https://github.com/hugofloresgarcia/vampnet2.git
pip install -e ./vampnet2

A note on Argbind

This repository relies on argbind to manage CLIs and config files. Config files are stored in the conf/ folder.

Usage

Staging a Run

Staging a run makes a copy of all the git-tracked files in the codebase and saves them to a folder for reproducibility. You can then run the training script from the staged folder.

coming soon

Training a model

python scripts/exp/train.py --args.load conf/vampnet.yml --save_path /path/to/checkpoints

Fine-tuning

To fine-tune a model, see the configuration files under conf/lora/. You just need to provide a list of audio files // folders to fine-tune on, then launch the training job as usual.

python scripts/exp/train.py --args.load conf/lora/birds.yml --save_path /path/to/checkpoints

Launching the Gradio Interface

python demo.py --args.load conf/interface/spotdl.yml --Interface.device cuda