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EuroLLM: Multilingual Language Models for Europe

About

The quality of open-weight LLMs has seen significant improvement, yet they remain predominantly focused on English. In this paper, we introduce the EuroLLM project, aimed at developing a suite of open-weight multilingual LLMs capable of understanding and generating text in all official European Union languages, as well as several additional relevant languages. We outline the progress made to date, detailing our data collection and filtering process, the development of scaling laws, the creation of our multilingual tokenizer, and the data mix and modeling configurations. Additionally, we release our initial models: EuroLLM-1.7B and EuroLLM-1.7B-Instruct and report their performance on multilingual general benchmarks and machine translation.

Pedro Henrique Martins, Patrick Fernandes, Jo\~ao Alves, Nuno M. Guerreiro, Ricardo Rei, Duarte M. Alves, Jos\'e Pombal, Amin Farajian, Manuel Faysse, Mateusz Klimaszewski, Pierre Colombo, Barry Haddow, Jos\'e G. C. de Souza, Alexandra Birch, Andr\'e F. T. Martins• 2024

Related benchmarks

TaskDatasetResultRank
Multi-task Language UnderstandingMMLU
Accuracy28.3
876
Instruction FollowingIFEval--
625
Commonsense ReasoningWinoGrande
Accuracy57.8
372
Science Question AnsweringARC Challenge
Accuracy35.9
342
Common Sense ReasoningHellaSwag
Accuracy45.9
213
Question AnsweringARC-C
Accuracy31.57
192
Science Question AnsweringARC Easy
Accuracy71.3
155
Multitask Language UnderstandingMMLU-Pro
Accuracy10.9
118
Commonsense ReasoningSocialIQA
Accuracy44.8
116
Emotional IntelligencePolish EQ-Bench
Overall Score54.1
106
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