Our Open Source Contributions

Over the years, we have published parts of our code and our AI models.

We have summarised these contributions on this page.

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Multilingual Passage Reranking Modell

  • This model is a reranking model trained by us, which can evaluate content according to various factors on an LLM basis.
  • It has been rated as one of the most efficient of its kind in various scientific papers:
  • It now has a medium, six-digit number of downloads

Hochqualitativer, deutscher Trainingsdatensatz

  • High-quality data sets are required to train AI models and avoid certain biases.
  • Together with Philipp May, T-Systems, we have defined this training dataset to train our LLMs.
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German Electra Model


  • Together with Philip May, T-Systems, we have published an improved Electra model, which was trained with 1.5 million steps.
  • At the time of publication, it was briefly the most efficient German-language LLM.

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