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[P] Headliner, a new sequence modeling library that eases the training and in particular, the deployment of custom sequence models

[P] Headliner, a new sequence modeling library that eases the training and in particular, the deployment of custom sequence models

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 (see figure 1). 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.

Figure 1: One example from our Welt.de headline generator.

We built this library with the following goals in mind:

🚀 Simple API for training and deployment (only a few lines of code)

➡️ Uses TensorFlow 2.0 with all its new features

⚙️ Modular classes: text preprocessing, modeling, evaluation and easily extensible for different encoder-decoder models

📄 Works 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, ⭐️ it on Github and spread the word! We’d love to get feedback. #deeplearning #machinelearning #NLP

🔤 Github: https://github.com/as-ideas/headliner

📚 Docs: https://as-ideas.github.io/headliner/

😎 Demo: https://github.com/as-ideas/headliner-demo

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