Progress Report: Towards European LLMs
We present preliminary results of the project OpenGPT-X. At present, the project has developed two multilingual large language models (LLMs) designed to embrace Europe's linguistic diversity by supporting all 24 official languages of the European Union. Trained on a dataset comprising around 60% non-English data and utilizing a custom multilingual tokenizer, our models address the limitations of existing LLMs that predominantly focus on English or a few high-resource languages. We detail the models' development principles, data processing techniques, tokenizer optimization, and training methodologies. The models demonstrate competitive performance across multilingual benchmarks, as evidenced by their performance on European versions of ARC, HellaSwag, MMLU, and TruthfulQA.
Institutions
- Forschungszentrum Jülich (DE)
- German Research Centre for Artificial Intelligence (DE)
- Fraunhofer Institute for Integrated Circuits (DE)
- Fraunhofer Institute for Intelligent Analysis and Information Systems (DE)
- Technische Universität Dresden (DE)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2024-10-01
- DOI
- https://doi.org/10.5281/zenodo.13866365
- Primary Topic
- Natural Language Processing Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00