Pretrained bullerengue-beta model for the Musika system for fast infinite waveform music generation. Introduced in this paper.

You can generate music from this pretrained bullerengue-beta model using the notebook available here.

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.