Caffe2 is a machine learning framework enabling simple and flexible deep learning. Building on the original Caffe, Caffe2 is designed with expression, speed, and modularity in mind, and allows a more flexible way to organize computation.


The CommAI project aims at developing new data-sets and algorithms to develop and evaluate general-purpose artificial agents that rely on a linguistic interface, and are capable of quickly adapting to a never-ending stream of tasks.


Self contained software accompanying the paper titled: Learning Longer Memory in Recurrent Neural Networks.


Code to reproduce results described in the paper “Sequence Level Training with RNNs” ICLR 2016.


Torch is a scientific computing framework with wide support for machine learning algorithms. It is easy to use and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C/CUDA implementation.

Stack RNN

Stack RNN is a project gathering the code from the paper Inferring Algorithmic Patterns with Stack-Augmented Recurrent Nets by Armand Joulin and Tomas Mikolov.


FastText is a library for text representation and classification.


The bAbI Project is organized towards the goal of automatic text understanding and reasoning.