MiLMMT-46-1B-Pretrain is a language model developed through continual pretraining of Gemma3-1B using a mix of 143 billion tokens from both monolingual and parallel data across 46 different languages. Please find more details in our paper:
Scaling Model and Data for Multilingual Machine Translation with Open Large Language Models.
We collect monolingual data from
DCAD-2000. For parallel data, we collect all Chinese-centric and English-centric parallel datasets from the
OPUS collection up to August 2025 and conduct a series of filtering processes, such as language identification, semantic duplication filtering, quality filtering, and more.
1@misc{shang2026scalingmodeldatamultilingual,
2 title={Scaling Model and Data for Multilingual Machine Translation with Open Large Language Models},
3 author={Yuzhe Shang and Pengzhi Gao and Wei Liu and Jian Luan and Jinsong Su},
4 year={2026},
5 eprint={2602.11961},
6 archivePrefix={arXiv},
7 primaryClass={cs.CL},
8 url={https://arxiv.org/abs/2602.11961},
9}
