Facebook’s another machine learning framework: Pytext

Facebook makes another machine learning framework open source. Pytext should make it easier to use Natural-Language-Processing in a production environment.

Facebook has released its natural language processing framework Pytext under an open source license. Pytext is based on Pytorch, which also comes from Facebook and is open source. Pytext is used in the social network, for example, for the operation of the portal and the so-called “M recommendations” in Messenger.

Natural language processing deals with the processing of human language. Above all, Facebook’s new framework is designed to help developers use machine learning faster in the development and production environments. According to a blog article, Facebook could bring new machine-learning models from experimental status into productive use within a few days.

NLP development

AI researchers and engineers have a wide and growing range of applications for systems that can understand our words. At Facebook, NLP is used to deliver more relevant content to people, provide powerful accessibility features, flag policy-violating posts, perform translations, and more. The state of the art in conversational AI is progressing rapidly, and PyText is helping us ship these new advancements more quickly, to improve the quality of our products. PyText is now implemented in Portal, our new video calling device, and in our M suggestions feature in Messenger. We are exploring other ways to use PyText in conversational AI. Pytext offers several benefits for NLP development:

  • A simplified workflow for faster experimentation.
  • Access to a rich set of prebuilt model architectures and utilities for text processing and vocabulary management to facilitate large-scale deployment.
  • The ability to harness the PyTorch ecosystem, including prebuilt models and tools created by researchers and engineers in the NLP community.

Pytext is supposed to help with the classification of documents and semantic parsing. It supports so-called multi-task modeling to train several machine-learning models at the same time.

Pytext already performs more than a billion operations a day

Most importantly, the Facebook framework should allow for low-latency work in order to work in real-time, which is one of Facebook’s requirements. In the social network, the framework already performs more than a billion operations a day.

Version 1.0 is now available under the BSD license on GitHub. In addition to the source code, there are already trained models and tutorials to get started.

Recent Articles

Frontend Tools 2019 survey: jQuery Threatened

Frontend Tools 2019 survey showed that React is voted the most important as well as the most widely used JavaScript tool. For the first...

PHP 8.0: Vote on Union Types ended

PHP 8.0 is scheduled for 2020. Recently, the PHP development team in PHP Internals voted on Union Types as a new feature for PHP....

Angular 9 Next versions: Bazel Schematics switched to Ivy

With Angular 9 next versions, the upcoming major version of the JavaScript framework has again received a number of feature updates, notably the innovations...

HP enters strategic partnership with ExpressVPN to increase security offerings on consumer laptops

In light of the recent challenges faced by the cryptocurrency space and the technological sphere at large, security has become a serious issue among...

Node.js 12.12: New flag for easier electron integration

Node.js 12.12 is here to bring a new flag to help work with embedders like Electron. In addition, source maps are now available for...

Related Stories

Leave A Reply

Please enter your comment!
Please enter your name here