---
license: apache-2.0
library_name: transformers
base_model: Qwen/Qwen3-4B
pipeline_tag: text-generation
tags:
  - moral reasoning
  - value reasoning
  - persona
  - chain-of-thought
language:
  - zh
---

# Model Card for MET-D-Qwen3-4B-zh-only

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.

## Model Details

- **Base model:** Qwen/Qwen3-4B
- **Task:** for a given `(situation, character description, action)` triple, answer two questions from the character's perspective:
  1. Is the action acceptable? (`Yes` / `No` / `Ambiguous`)
  2. Would (not) doing it be emotionally/mentally discomforting? (`Yes` / `No`)
- **Training data:** self-generated reasoning traces, rejection-sampled against the ground truth per character perspective, in Chinese only
- **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).
- **License:** Apache 2.0 (inherited from the base model)

## How to Get Started

```python
from transformers import AutoTokenizer
from vllm import LLM, SamplingParams

model_id = "launch/MET-D-Qwen3-4B-zh-only"
tokenizer = AutoTokenizer.from_pretrained(model_id)
llm = LLM(model=model_id, max_model_len=16384)

situation = "..."            # the moral dilemma narrative
character = "..."            # the character description
action = "..."                # the candidate action to judge

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。
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"。
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。
对于全部的两个问题，你必须确保同时输出"原因："和"回答"。

道德困境:
{situation}

角色性格描述:
{character}

问题:
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}"
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？

你的回答：
1. 原因: {{原因}} 回答: {{是/否/不确定}}
2. 原因: {{原因}} 回答: {{是/否}}
"""

chat_prompt = tokenizer.apply_chat_template(
    [{"role": "user", "content": prompt}],
    tokenize=False,
    add_generation_prompt=True,
)

sampling_params = SamplingParams(temperature=0.0, max_tokens=2048)
outputs = llm.generate(chat_prompt, sampling_params)
print(outputs[0].outputs[0].text)
```

## Model Variants

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:

| 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 |

## Citation

If you use this, please cite:

```bibtex
@article{lee2026met,
  title={MET: Theory-Grounded and Culture-Aware Multilingual Moral Reasoning},
  author={Lee, Ayoung and Kwon, Ryan and Zhang, Yunxiang and Liu, Yuxuan and Railton, Peter and Wang, Lu},
  journal={arXiv preprint arXiv:2607.11736},
  year={2026}
}
```