---
license: mit
thumbnail: "https://iscale.iheart.com/catalog/album/46707655"
tags:
- audio
- music
- generation
- tensorflow
---

# Musika Model: musika-grateful-dead-barton-hall
## Model provided by: benwakefield

Pretrained model for the [Musika system](https://github.com/marcoppasini/musika) for fast infinite waveform music generation.
Introduced in [this paper](https://arxiv.org/abs/2208.08706).

Trained on the [Cornell 5/8/77](https://en.wikipedia.org/wiki/Cornell_5/8/77) show performed by the Grateful Dead.

## How to use

You can generate music from this model using the notebook available [here](https://colab.research.google.com/drive/1HJWliBXPi-Xlx3gY8cjFI5-xaZgrTD7r).

### Model description

This pretrained GAN system consists of a ResNet-style generator and discriminator. During training, stability is controlled by adapting the strength of gradient penalty regularization on-the-fly. The gradient penalty weighting term is contained in *switch.npy*. The generator is conditioned on a latent coordinate system to produce samples of arbitrary length. The latent representations produced by the generator are then passed to a decoder which converts them into waveform audio.
The generator has a context window of about 12 seconds of audio.