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(situation, character description, action) triple, answer two questions from the character's perspective:
Yes / No / Ambiguous)Yes / No)1from transformers import AutoTokenizer
2from vllm import LLM, SamplingParams
3
4model_id = "launch/MET-D-Qwen3-4B-zh-only"
5tokenizer = AutoTokenizer.from_pretrained(model_id)
6llm = LLM(model=model_id, max_model_len=16384)
7
8situation = "..." # the moral dilemma narrative
9character = "..." # the character description
10action = "..." # the candidate action to judge
11
12prompt = f"""我会给你提供一个道德困境,并提供一个角色性格描述及其对应的一些问题。
13第一个问题的回答应该为"是","否"或者"不确定"。第二个问题的回答应该为"是"或"否"。
14因为你的回答会被自动分割,所以你必须严格遵守回答的格式规定。
15对于全部的两个问题,你必须确保同时输出"原因:"和"回答"。
16
17道德困境:
18{situation}
19
20角色性格描述:
21{character}
22
23问题:
241. 从 A的角度来说,下面的行动——此行动已经采取、考虑被采取、可能考虑被采取、或在情境的内容中被质疑——是可接受的?"{action}"
252. 如果前者的回答为是,A 是否会因采取该行动而在情绪或精神上感觉不适?相反地,如果前者回答为否,A 是否会因为不采取该行动而在情绪或精神上感觉不适?
26
27你的回答:
281. 原因: {{原因}} 回答: {{是/否/不确定}}
292. 原因: {{原因}} 回答: {{是/否}}
30"""
31
32chat_prompt = tokenizer.apply_chat_template(
33 [{"role": "user", "content": prompt}],
34 tokenize=False,
35 add_generation_prompt=True,
36)
37
38sampling_params = SamplingParams(temperature=0.0, max_tokens=2048)
39outputs = llm.generate(chat_prompt, sampling_params)
40print(outputs[0].outputs[0].text)| Repo | Base model | Language(s) |
|---|---|---|
launch/MET-D-Qwen3-4B | Qwen3-4B | all 6 (mixed) |
launch/MET-D-Qwen3-4B-en-only | Qwen3-4B | English only |
launch/MET-D-Qwen3-4B-es-only | Qwen3-4B | Spanish only |
launch/MET-D-Qwen3-4B-hi-only | Qwen3-4B | Hindi only |
launch/MET-D-Qwen3-4B-ko-only | Qwen3-4B | Korean only |
launch/MET-D-Qwen3-4B-ms-only | Qwen3-4B | Malay only |
launch/MET-D-Qwen3-4B-zh-only | Qwen3-4B | Chinese only |
launch/MET-D-Qwen3-8B | Qwen3-8B | all 6 (mixed) |
launch/MET-D-Qwen3-8B-en-only | Qwen3-8B | English only |
launch/MET-D-Gemma3-4B | Gemma-3-4B-it | all 6 (mixed) |
launch/MET-D-Gemma3-4B-en-only | Gemma-3-4B-it | English only |
1@article{lee2026met,
2 title={MET: Theory-Grounded and Culture-Aware Multilingual Moral Reasoning},
3 author={Lee, Ayoung and Kwon, Ryan and Zhang, Yunxiang and Liu, Yuxuan and Railton, Peter and Wang, Lu},
4 journal={arXiv preprint arXiv:2607.11736},
5 year={2026}
6}