Tensor2Tensor vs cnvrg.io

Tensor2Tensor vs cnvrg.io: What are the differences?

Developers describe Tensor2Tensor as "Library of deep learning models & datasets designed to make deep learning more accessible (by Google Brain)". It is a library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research. It was developed by researchers and engineers in the Google Brain team and a community of users. On the other hand, cnvrg.io is detailed as "An end-to-end machine learning platform to build and deploy AI models at scale". It is an AI OS, transforming the way enterprises manage, scale and accelerate AI and data science development from research to production. The code-first platform is built by data scientists, for data scientists and offers unrivaled flexibility to run on-premise or cloud.

Tensor2Tensor and cnvrg.io can be primarily classified as "Machine Learning" tools.

Some of the features offered by Tensor2Tensor are:

• Many state of the art and baseline models are built-in and new models can be added easily
• Many datasets across modalities - text, audio, image - available for generation and use, and new ones can be added easily
• Models can be used with any dataset and input mode (or even multiple)

On the other hand, cnvrg.io provides the following key features:

• Machine Learning Pipelines
• AI Library
• Open Compute

Tensor2Tensor is an open source tool with 10.2K GitHub stars and 2.6K GitHub forks. Here's a link to Tensor2Tensor's open source repository on GitHub.