NeROIC VS jukebox

Compare NeROIC vs jukebox and see what are their differences.

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NeROIC jukebox
4 129
910 7,571
3.3% 0.5%
0.0 0.0
over 1 year ago 2 months ago
Python Python
GNU General Public License v3.0 or later GNU General Public License v3.0 or later
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

NeROIC

Posts with mentions or reviews of NeROIC. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-09-29.

jukebox

Posts with mentions or reviews of jukebox. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-10-02.

What are some alternatives?

When comparing NeROIC and jukebox you can also consider the following projects:

make-a-video-pytorch - Implementation of Make-A-Video, new SOTA text to video generator from Meta AI, in Pytorch

lucid-sonic-dreams

text2mesh - 3D mesh stylization driven by a text input in PyTorch

ultimatevocalremovergui - GUI for a Vocal Remover that uses Deep Neural Networks.

Clip-Forge

spleeter - Deezer source separation library including pretrained models.

music-demixing-challenge-starter-kit - Starter kit for getting started in the Music Demixing Challenge.

dalle-mini - DALL·E Mini - Generate images from a text prompt

latent-diffusion - High-Resolution Image Synthesis with Latent Diffusion Models

gpt-2 - Code for the paper "Language Models are Unsupervised Multitask Learners"

ALAE - [CVPR2020] Adversarial Latent Autoencoders

musiclm-pytorch - Implementation of MusicLM, Google's new SOTA model for music generation using attention networks, in Pytorch