| --- |
| license: gemma |
| license_name: license |
| license_link: LICENSE |
| base_model: |
| - google/gemma-2-2b |
| pipeline_tag: translation |
| library_name: transformers |
| language: |
| - ar |
| - bn |
| - cs |
| - de |
| - en |
| - es |
| - fa |
| - fr |
| - he |
| - hi |
| - id |
| - it |
| - ja |
| - km |
| - ko |
| - lo |
| - ms |
| - my |
| - nl |
| - pl |
| - pt |
| - ru |
| - th |
| - tl |
| - tr |
| - ur |
| - vi |
| - zh |
| --- |
| |
|
|
|
|
| ## Model Description |
| GemmaX2-28-2B-Pretrain is a language model developed through continual pretraining of Gemma2-2B using a mix of 56 billion tokens from both monolingual and parallel data across 28 different languages. Please find more details in our paper: [Multilingual Machine Translation with Open Large Language Models at Practical Scale: An Empirical Study](https://arxiv.org/pdf/2502.02481). |
|
|
| - **Developed by:** Xiaomi |
| - **Model type:** GemmaX2-28-2B-Pretrain is obtained by continually pretraining Gemma2-2B on a large amount of monolingual and parallel data. Subsequently, GemmaX2-28-2B-v0.1 is derived through supervised finetuning on a small set of high-quality translation instruction data. |
| - **Languages:** Arabic, Bengali, Czech, German, English, Spanish, Persian, French, Hebrew, Hindi, Indonesian, Italian, Japanese, Khmer, Korean, Lao, Malay, Burmese, Dutch, Polish, Portuguese, Russian, Thai, Tagalog, Turkish, Urdu, Vietnamese, Chinese. |
| - **Github:** Please find more details in our [Github repository](https://github.com/xiaomi-research/gemmax). |
|
|
|
|
| **Note that GemmaX2-28-2B-Pretrain is NOT translation model.** |
|
|
|
|
| ## Training Data |
|
|
| We collect monolingual data from [CulturaX](https://huggingface.co/datasets/uonlp/CulturaX) and [MADLAD-400](https://huggingface.co/datasets/allenai/MADLAD-400). For parallel data, we collect all Chinese-centric and English-centric parallel datasets from the [OPUS](https://opus.nlpl.eu/) collection up to August 2024 and conduct a series of filtering processes, such as language identification, semantic duplication filtering, quality filtering, and more. |
|
|
|
|
| ## Citation |
|
|
| ```bibtex |
| @misc{cui2025multilingualmachinetranslationopen, |
| title={Multilingual Machine Translation with Open Large Language Models at Practical Scale: An Empirical Study}, |
| author={Menglong Cui and Pengzhi Gao and Wei Liu and Jian Luan and Bin Wang}, |
| year={2025}, |
| eprint={2502.02481}, |
| archivePrefix={arXiv}, |
| primaryClass={cs.CL}, |
| url={https://arxiv.org/abs/2502.02481}, |
| } |
| ``` |
