Code for the paper "Jukebox: A Generative Model for Music"
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Updated
May 3, 2024 - Python
Code for the paper "Jukebox: A Generative Model for Music"
Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)
Vector Quantized VAEs - PyTorch Implementation
PyTorch implementation of VQ-VAE by Aäron van den Oord et al.
Minimalist implementation of VQ-VAE in Pytorch
Easy generative modeling in PyTorch.
PyTorch implementation of VQ-VAE + WaveNet by [Chorowski et al., 2019] and VQ-VAE on speech signals by [van den Oord et al., 2017]
(CVPR 2023) Pytorch implementation of “T2M-GPT: Generating Human Motion from Textual Descriptions with Discrete Representations”
VQ-VAE for Acoustic Unit Discovery and Voice Conversion
Vector-Quantized Contrastive Predictive Coding for Acoustic Unit Discovery and Voice Conversion
Pytorch implementation of stochastically quantized variational autoencoder (SQ-VAE)
CVPR 2021: "Generating Diverse Structure for Image Inpainting With Hierarchical VQ-VAE"
A Chainer implementation of VQ-VAE.
Python toolkit for speech processing
PyTorch implementation of VQ-VAE-2 from "Generating Diverse High-Fidelity Images with VQ-VAE-2"
A PyTorch implementation of "Continuous Relaxation Training of Discrete Latent Variable Image Models"
Official Implement of Multi-Stage Multi-Codebook (MSMC) TTS
Pytorch Implementation of "Neural Discrete Representation Learning"
[ICML 2023] Official PyTorch Implementation of "Hierarchical Neural Coding for Controllable CAD Model Generation".
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