OpenMined / SyferText

A privacy preserving NLP framework
Apache License 2.0
198 stars 49 forks source link
encrypted-computation federated-learning hacktoberfest hacktoberfest2020 natural-language-processing nlp python secure-multiparty-computation

CI License Python 3.6

All Contributors

SyferText

SyferText is a library for privacy preserving Natural Language Processing in Python. It leverages PySyft to perform Federated Learning and Encrypted Computations ( Multi-Party Computation (MPC) on text data. The two main usage scenarios of SyferText are:

To get a more detailed introduction about SyferText, watch :movie_camera: OpenMined AMA with Alan Aboudib available on YouTube.

Installation

You can install SyferText by directly cloning this repo:

$ git clone https://github.com/OpenMined/SyferText.git
$ cd SyferText
$ python setup.py install

That's it, you are good to go!

Getting Started

SyferText can be used to work with datasets residing on a local machine (or a local worker as we call it in PySyft), as well as with private datasets on remote workers. Here is a list of tutorials that you can follow to get more familiar with SyferText:

More tutorials are coming soon. Stay tuned!

Our Team

SyferText is created and maintained by the NLP team at OpenMined and by volunteer contributors from all around the world. Here are the current members of the core NLP team. The team is growing!


Alan Aboudib avatar
Alan Aboudib

Team Lead / Author
Nilansh Rajput avatar
Nilansh Rajput

OM NLP team / Core Dev
Jatin Prakash avatar
Jatin Prakash

OM NLP team / Core Dev

Ramesht Shukla

OM NLP Team / Core Dev
Hersh Dhillon avatar
Hersh Dhillon

OM NLP team / Core Dev


Events

Demo on remote blind tokenization with SyferText.

Demo on sentiment analysis with SyferText on multiple private datasets.

SyferText vision and encrypted sentiment analyzer demo.

Introduction to SyferText.

SyferText vision and encrypted sentiment analyzer demo.

About SyferText and my Open Source Contribution Experience with OpenMined

News

To get news about feature and tutorial relseases:

Alan Aboudib: @twitter

and join #lib_syfertext channel on slack.

Support

To get support in using this library, please join the #lib_syfertext Slack channel. If you’d like to follow along with any code changes to the library, please join the #code_syfertext Slack channel. Click here to join our Slack community!

Contact Us

You can reach out to us by contacting Alan on one of the following channels:

LinkedIn | Slack | Twitter

License

Apache License 2.0