Author: Florian Berding, Yuliia Tykhonova, Julia Pargmann, Andreas Slopinski, Elisabeth Riebenbauer, Karin Rebmann

# A02 Supported Base Models

#### Florian Berding, Yuliia Tykhonova, Julia Pargmann, Andreas Slopinski, Elisabeth Riebenbauer, Karin Rebmann

> All models created with ‘aifeducation’ do not need ‘sentencepiece’ even if this requirment is displayed in the table. ‘aifeducation’ uses a WordPieceTokenizer for all newly created models.

BaseModel | Reference | Require Sentencepiece
--- | --- | ---
BaseModelAlbert | Lan, Z., Chen, M., Goodman, S., Gimpel, K., Sharma, P., & Soricut, R. (2019). ALBERT; A Lite BERT for Self-supervised Learning of Language Representations. arXiv. doi: 10.48550/ARXIV.1909.11942 | TRUE
BaseModelBert | Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2019). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In J. Burstein, C. Doran, & T. Solorio (Eds.), Proceedings of the 2019 Conference of the North (pp. 4171–4186). Association for Computational Linguistics. doi: 10.18653/v1/N19-1423 | FALSE
BaseModelDebertaV2 | He, P., Liu, X., Gao, J. & Chen, W. (2020). DeBERTa: Decoding-enhanced BERT with Disentangled Attention. doi: 10.48550/arXiv.2006.03654 | FALSE
BaseModelDistilBERT | Asnh, V., Debut, L., Chaumond, J. & Wolf, T. (2019). DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter. doi: 10.48550/arXiv.1910.01108 | FALSE
BaseModelEuroBert | Boizard, N., Gisserot-Boukhlef, H., Alves, D. M., Martins, A., Hammal, A., Corro, C., Hudelot, C., Malherbe, E., Malaboeuf, E., Jourdan, F., Hautreux, G., Alves, J., El-Haddad, K., Faysse, M., Peyrard, M., Guerreiro, N. M., Fernandes, P., Rei, R. & Colombo, P. (2025). EuroBERT: Scaling Multilingual Encoders for European Languages. doi: 10.48550/arXiv.2503.05500 | FALSE
BaseModelFunnel | Dai, Z., Lai, G., Yang, Y. & Le, Q. V. (2020). Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing. doi: 10.48550/arXiv.2006.03236 | FALSE
BaseModelMPNet | Song,K., Tan, X., Qin, T., Lu, J. & Liu, T.-Y. (2020). MPNet: Masked and Permuted Pre-training for Language Understanding. doi: 10.48550/arXiv.2004.09297 | FALSE
BaseModelModernBert | Warner, B., Chaffin, A., Clavie, B., Weller, O., Hallstroem, O., Taghadouini, S., Gallagher, A., Biswas, R., Ladhak, F., Aarsen, T., Cooper, N., Adams, G., Howard, J. & Poli, I. (2024). Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference. doi: 10.48550/arXiv.2412.13663 | FALSE
BaseModelRoberta | Liu, Y., Ott, M., Goyal, N., Du, J., Joshi, M., Chen, D., Levy, O., Lewis, M., Zettlemoyer, L., & Stoyanov, V. (2019). RoBERTa: A Robustly Optimized BERT Pretraining Approach. doi: 10.48550/arXiv.1907.11692 | FALSE
BaseModelRobertaXML | Conneau, A., Khandelwal, K., Goyal, N., Chaudhary, V., Wenzek, G., Guzman, F., Grave, E., Ott, M., Zettlemoyer, L., & Stoyanov, V. (2019). Unsupervised Cross-lingual Representation Learning at Scale. doi: 10.48550/arXiv.1911.02116 | TRUE
BaseModelXmod | Pfeiffer, J., Goyal, N., Lin, X. V., Li, X., Cross, J., Riedel, S., & Artetxe, M. (2022). Lifting the Curse of Multilinguality by Pre-training Modular Transformers. arXiv. doi: 10.48550/arXiv.2205.06266 | TRUE