Code for the paper "Jukebox: A Generative Model for Music"

Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)

Implementation of Generating Diverse High-Fidelity Images with VQ-VAE-2 in PyTorch

Vector Quantized VAEs - PyTorch Implementation

(CVPR 2023) Pytorch implementation of “T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations”

Minimalist implementation of VQ-VAE in Pytorch

Easy generative modeling in PyTorch

VQ-VAE for Acoustic Unit Discovery and Voice Conversion

PyTorch implementation of VQ-VAE + WaveNet by [Chorowski et al., 2019] and VQ-VAE on speech signals by [van den Oord et al., 2017]

Pytorch implementation of stochastically quantized variational autoencoder (SQ-VAE)

CVPR 2021: "Generating Diverse Structure for Image Inpainting With Hierarchical VQ-VAE"

Official Implement of Multi-Stage Multi-Codebook (MSMC) TTS

Vector-Quantized Contrastive Predictive Coding for Acoustic Unit Discovery and Voice Conversion

PyTorch implementation of VQ-VAE-2 from "Generating Diverse High-Fidelity Images with VQ-VAE-2"

L-Verse: Bidirectional Generation Between Image and Text

[ICML 2023] Official PyTorch Implementation of "Hierarchical Neural Coding for Controllable CAD Model Generation".

A Chainer implementation of VQ-VAE.

Python toolkit for speech processing

This repo implements VQVAE on mnist and as well as colored version of mnist images. It also implements simple LSTM for generating sample numbers using the encoder outputs of trained VQVAE

A Bach music generator with Artificial Intelligence. This model is made by a VQ-VAE + Transformer (decoder-only). Sequences of midi 1 quarter length are compressed into 16 codebooks via VQ-VAE and a transformer learns how to generate the codebooks sequence to obtain a midi score.