We've just open-sourced our library headliner which is a sequence modeling library that eases the training and in particular, the deployment of custom sequence models. It was originally built for our own research at Axel Springer AI to generate headlines from Welt news articles. That's why we chose the name, Headliner. Although this library was created internally to generate headlines, you can also use it for other tasks like machine translations, text summarization and many more.
We built this library with the following goals in mind. Firstly, it offers a simple API for training and deployment of models (only a few lines of code). Secondly, it uses TensorFlow 2.0 with all its new features. Thirdly, it has modular classes: text preprocessing, modeling, evaluation and is easily extensible for new models and finally works well on large text data.
Headliner is our first NLP project that we open-sourced and we're happy about this. Please try out our library, star it on Github and spread the word! We'd love to get feedback.
We built this library with the following goals in mind. Firstly, it offers a simple API for training and deployment of models (only a few lines of code). Secondly, it uses TensorFlow 2.0 with all its new features. Thirdly, it has modular classes: text preprocessing, modeling, evaluation and is easily extensible for new models and finally works well on large text data.
Headliner is our first NLP project that we open-sourced and we're happy about this. Please try out our library, star it on Github and spread the word! We'd love to get feedback.