初始化项目，由ModelHub XC社区提供模型
Model: NiuTrans/LMT-60-8B Source: Original Platform
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README.md
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README.md
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---
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base_model:
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- NiuTrans/LMT-60-8B-Base
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datasets:
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- NiuTrans/LMT-60-sft-data
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language:
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- en
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- zh
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- ar
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- es
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- de
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- fr
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- it
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- ja
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- nl
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- pl
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- pt
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- ru
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- tr
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- bg
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- bn
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- cs
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- da
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- el
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- fa
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- fi
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- hi
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- hu
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- id
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- ko
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- nb
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- ro
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- sk
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- sv
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- th
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- uk
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- vi
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- am
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- az
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- bo
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- he
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- hr
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- hy
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- is
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- jv
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- ka
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- kk
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- km
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- ky
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- lo
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- mvf
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- mr
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- ms
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- my
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- ne
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- ps
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- si
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- sw
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- ta
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- te
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- tg
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- tl
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- ug
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- ur
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- uz
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- yue
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license: apache-2.0
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metrics:
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- bleu
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- comet
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pipeline_tag: translation
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library_name: transformers
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---
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## LMT
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- Paper: [NiuTrans.LMT: Toward Inclusive and Scalable Multilingual Machine Translation with LLMs](https://arxiv.org/abs/2511.07003)
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- Github: [LMT](https://github.com/NiuTrans/LMT)
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**LMT-60** is a suite of **Chinese-English-centric** Multilingual Machine Translation (MMT) models trained on **90B tokens** mixed monolingual and bilingual tokens, covering **60 languages across 234 translation directions** and achieving **SOTA performance** among models with similar language coverage.
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We release both the CPT and GRPO versions of LMT-60 in four sizes (0.6B/1.7B/4B/8B). All checkpoints are available:
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| Models | Model Link |
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|:------------|:------------|
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| LMT-60-0.6B-Base | [NiuTrans/LMT-60-0.6B-Base](https://huggingface.co/NiuTrans/LMT-60-0.6B-Base) |
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| LMT-60-0.6B | [NiuTrans/LMT-60-0.6B](https://huggingface.co/NiuTrans/LMT-60-0.6B) |
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| LMT-60-1.7B-Base | [NiuTrans/LMT-60-1.7B-Base](https://huggingface.co/NiuTrans/LMT-60-1.7B-Base) |
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| LMT-60-1.7B | [NiuTrans/LMT-60-1.7B](https://huggingface.co/NiuTrans/LMT-60-1.7B) |
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| LMT-60-4B-Base | [NiuTrans/LMT-60-4B-Base](https://huggingface.co/NiuTrans/LMT-60-4B-Base) |
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| LMT-60-4B | [NiuTrans/LMT-60-4B](https://huggingface.co/NiuTrans/LMT-60-4B) |
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| LMT-60-8B-Base | [NiuTrans/LMT-60-8B-Base](https://huggingface.co/NiuTrans/LMT-60-8B-Base) |
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| LMT-60-8B | [NiuTrans/LMT-60-8B](https://huggingface.co/NiuTrans/LMT-60-8B) |
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Our supervised fine-tuning (SFT) data are released at [NiuTrans/LMT-60-sft-data](https://huggingface.co/datasets/NiuTrans/LMT-60-sft-data)
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## Quickstart
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_name = "NiuTrans/LMT-60-8B"
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tokenizer = AutoTokenizer.from_pretrained(model_name, padding_side='left')
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model = AutoModelForCausalLM.from_pretrained(model_name)
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prompt = """Translate the following text from English into Chinese:
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English: The concept came from China where plum blossoms were the flower of choice.
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Chinese:"""
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messages = [{"role": "user", "content": prompt}]
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text = tokenizer.apply_chat_template(
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messages,
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tokenize=False,
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add_generation_prompt=True,
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)
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model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
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generated_ids = model.generate(**model_inputs, max_new_tokens=512, num_beams=5, do_sample=False)
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output_ids = generated_ids[0][len(model_inputs.input_ids[0]):].tolist()
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outputs = tokenizer.decode(output_ids, skip_special_tokens=True)
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print("response:", outputs)
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```
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## Support Languages
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| Resource Tier | Languages |
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| :---- | :---- |
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| High-resource Languages (13) | Arabic(ar), English(en), Spanish(es), German(de), French(fr), Italian(it), Japanese(ja), Dutch(nl), Polish(pl), Portuguese(pt), Russian(ru), Turkish(tr), Chinese(zh) |
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| Medium-resource Languages (18) | Bulgarian(bg), Bengali(bn), Czech(cs), Danish(da), Modern Greek(el), Persian(fa), Finnish(fi), Hindi(hi), Hungarian(hu), Indonesian(id), Korean(ko), Norwegian Bokmål(nb), Romanian(ro), Slovak(sk), Swedish(sv), Thai(th), Ukrainian(uk), Vietnamese(vi) |
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| Low-resouce Languages (29) | Amharic(am), Azerbaijani(az), Tibetan(bo), Modern Hebrew(he), Croatian(hr), Armenian(hy), Icelandic(is), Javanese(jv), Georgian(ka), Kazakh(kk), Central Khmer(km), Kirghiz(ky), Lao(lo), Inner Mongolian(mvf), Marathi(mr), Malay(ms), Burmese(my), Nepali(ne), Pashto(ps), Sinhala(si), Swahili(sw), Tamil(ta), Telugu(te), Tajik(tg), Tagalog(tl), Uighur(ug), Urdu(ur), Uzbek(uz), Yue Chinese(yue) |
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## Citation
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If you find our paper useful for your research, please kindly cite our paper:
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```bash
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@misc{luoyf2025lmt,
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title={NiuTrans.LMT: Toward Inclusive and Scalable Multilingual Machine Translation with LLMs},
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author={Yingfeng Luo, Ziqiang Xu, Yuxuan Ouyang, Murun Yang, Dingyang Lin, Kaiyan Chang, Tong Zheng, Bei Li, Peinan Feng, Quan Du, Tong Xiao, Jingbo Zhu},
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year={2025},
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eprint={2511.07003},
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2511.07003},
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}
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```
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