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1Translate this from <source language name> to <target language name>:
2<source language name>: <source language sentence>
3<target language name>:1from vllm import LLM, SamplingParams
2
3
4model_id = "xiaomi-research/MiLMMT-46-4B-v1.0"
5
6model = LLM(model=model_id)
7sampling_params = SamplingParams(top_k=1, temperature=0, max_tokens=2048)
8
9text = "Translate this from Chinese (Simplified) to English:\nChinese (Simplified): 我爱机器翻译\nEnglish:"
10
11outputs = model.generate(text, sampling_params)
12print(outputs[0].outputs[0].text)1from transformers import AutoModelForCausalLM, AutoTokenizer
2
3
4model_id = "xiaomi-research/MiLMMT-46-4B-v1.0"
5
6model = AutoModelForCausalLM.from_pretrained(model_id)
7tokenizer = AutoTokenizer.from_pretrained(model_id)
8
9text = "Translate this from Chinese (Simplified) to English:\nChinese (Simplified): 我爱机器翻译\nEnglish:"
10inputs = tokenizer(text, add_special_tokens=False, return_tensors="pt")
11
12outputs = model.generate(**inputs, max_new_tokens=1024)
13print(tokenizer.decode(outputs[0], skip_special_tokens=True))1@misc{han2026referencefreeposttrainingopenlarge,
2 title={Reference-Free Post-Training of Open Large Language Models for Multilingual Machine Translation},
3 author={Chris Han and Pengzhi Gao and Pei Fu and Jian Luan},
4 year={2026},
5 eprint={2608.10812},
6 archivePrefix={arXiv},
7 primaryClass={cs.CL},
8 url={https://arxiv.org/abs/2608.10812},
9}