104 lines
4.6 KiB
Markdown
104 lines
4.6 KiB
Markdown
---
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license: apache-2.0
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library_name: transformers
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base_model: Qwen/Qwen3-4B
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pipeline_tag: text-generation
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tags:
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- moral reasoning
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- value reasoning
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- persona
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- chain-of-thought
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language:
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- zh
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---
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# Model Card for MET-D-Qwen3-4B-zh-only
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MET-D-Qwen3-4B-zh-only is a Chinese-only moral reasoning model fine-tuned from [Qwen3-4B](https://huggingface.co/Qwen/Qwen3-4B). Given a moral dilemma, a character description, and a candidate action, it judges the action from that character's perspective and explains its judgment with an explicit chain-of-thought before answering. Moral dilemmas rarely have a single correct answer, which makes reasoning traces hard to verify. We address this by introducing a character perspective that yields a ground-truth answer, which is used for rejection-sampling the model's own reasoning traces, conditioned on a per-language, per-situation selection of theoretical grounds. Both the reasoning trace and the final answer are generated in Chinese.
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## Model Details
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- **Base model:** Qwen/Qwen3-4B
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- **Task:** for a given `(situation, character description, action)` triple, answer two questions from the character's perspective:
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1. Is the action acceptable? (`Yes` / `No` / `Ambiguous`)
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2. Would (not) doing it be emotionally/mentally discomforting? (`Yes` / `No`)
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- **Training data:** self-generated reasoning traces, rejection-sampled against the ground truth per character perspective, in Chinese only
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- **Language coverage:** this checkpoint is trained on **Chinese only**. The multilingual model and other single-language variants are also available (see [Model Variants](#model-variants) below).
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- **License:** Apache 2.0 (inherited from the base model)
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## How to Get Started
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```python
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from transformers import AutoTokenizer
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from vllm import LLM, SamplingParams
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model_id = "launch/MET-D-Qwen3-4B-zh-only"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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llm = LLM(model=model_id, max_model_len=16384)
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situation = "..." # the moral dilemma narrative
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character = "..." # the character description
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action = "..." # the candidate action to judge
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prompt = 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。
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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"。
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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。
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对于全部的两个问题，你必须确保同时输出"原因："和"回答"。
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道德困境:
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{situation}
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角色性格描述:
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{character}
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问题:
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1. 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}"
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2. 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？
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你的回答：
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1. 原因: {{原因}} 回答: {{是/否/不确定}}
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2. 原因: {{原因}} 回答: {{是/否}}
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"""
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chat_prompt = tokenizer.apply_chat_template(
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[{"role": "user", "content": prompt}],
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tokenize=False,
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add_generation_prompt=True,
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)
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sampling_params = SamplingParams(temperature=0.0, max_tokens=2048)
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outputs = llm.generate(chat_prompt, sampling_params)
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print(outputs[0].outputs[0].text)
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```
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## Model Variants
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This checkpoint is part of the [MET collection](https://huggingface.co/collections/launch/met), which includes the same task across base models and language subsets:
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| Repo | Base model | Language(s) |
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|---|---|---|
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| `launch/MET-D-Qwen3-4B` | Qwen3-4B | all 6 (mixed) |
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| `launch/MET-D-Qwen3-4B-en-only` | Qwen3-4B | English only |
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| `launch/MET-D-Qwen3-4B-es-only` | Qwen3-4B | Spanish only |
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| `launch/MET-D-Qwen3-4B-hi-only` | Qwen3-4B | Hindi only |
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| `launch/MET-D-Qwen3-4B-ko-only` | Qwen3-4B | Korean only |
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| `launch/MET-D-Qwen3-4B-ms-only` | Qwen3-4B | Malay only |
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| `launch/MET-D-Qwen3-4B-zh-only` | Qwen3-4B | Chinese only |
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| `launch/MET-D-Qwen3-8B` | Qwen3-8B | all 6 (mixed) |
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| `launch/MET-D-Qwen3-8B-en-only` | Qwen3-8B | English only |
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| `launch/MET-D-Gemma3-4B` | Gemma-3-4B-it | all 6 (mixed) |
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| `launch/MET-D-Gemma3-4B-en-only` | Gemma-3-4B-it | English only |
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## Citation
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If you use this, please cite:
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```bibtex
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@article{lee2026met,
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title={MET: Theory-Grounded and Culture-Aware Multilingual Moral Reasoning},
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author={Lee, Ayoung and Kwon, Ryan and Zhang, Yunxiang and Liu, Yuxuan and Railton, Peter and Wang, Lu},
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journal={arXiv preprint arXiv:2607.11736},
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year={2026}
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}
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```
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