Facebook posts its fast and accurate ConvNet models for machine translation on GitHub

In its latest paper, the Facebook AI Research (FAIR) team dropped some impressive results for its implementation of a modified convolutional neural network for machine translation. Facebook says it has achieved a small bump in accuracy at nine times the speed of traditional recurrent network models. And to complement its research, the company is releasing its pre-trained models on GitHub, along with all the tools needed to replicate the results on your own. When most of us think of machine translation, we think of Google Translate (sorry Facebook and my 8th grade Spanish teacher). But while that is certainly the most well-known implementation, Facebook relies on the technology extensively for translating posts on News Feed, among other uses.