license, library_name, base_model, pipeline_tag, tags, language
license
library_name
base_model
pipeline_tag
tags
language
apache-2.0
transformers
Qwen/Qwen3-4B
text-generation
moral reasoning
value reasoning
persona
chain-of-thought
es
Model Card for MET-D-Qwen3-4B-es-only
MET-D-Qwen3-4B-es-only is a Spanish-only moral reasoning model fine-tuned from 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 Spanish.
Model Details
Base model: Qwen/Qwen3-4B
Task: for a given (situation, character description, action) triple, answer two questions from the character's perspective:
Is the action acceptable? (Yes / No / Ambiguous)
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 Spanish only
Language coverage: this checkpoint is trained on Spanish only. The multilingual model and other single-language variants are also available (see Model Variants below).
License: Apache 2.0 (inherited from the base model)
How to Get Started
fromtransformersimportAutoTokenizerfromvllmimportLLM,SamplingParamsmodel_id="launch/MET-D-Qwen3-4B-es-only"tokenizer=AutoTokenizer.from_pretrained(model_id)llm=LLM(model=model_id,max_model_len=16384)situation="..."# the moral dilemma narrativecharacter="..."# the character descriptionaction="..."# the candidate action to judgeprompt=f"""Te propondré un dilema moral y te presentaré una descripción del personaje y preguntas.
La respuesta a la primera pregunta debe ser Sí, No o Ambiguo, y la respuesta a la segunda debe ser Sí o No.
Debes respetar estrictamente el formato de salida, ya que se analizará automáticamente.
Asegúrate de mostrar tanto la "Razón:" como la "Respuesta:" para las dos preguntas.
Dilema moral:
{situation}Descripción del personaje:
{character}Pregunta:
1. Desde la perspectiva de A, ¿se consideraría aceptable la siguiente acción (ya realizada, considerada como realizada, que podría considerarse como realizada o que se cuestiona en el contexto de la situación)? "{action}"
2. Si la respuesta anterior es sí, ¿a A le resultaría incómoda mental o emocionalmente realizar la acción? Por el contrario, si la respuesta anterior es no, ¿a A le resultaría incómoda mental o emocionalmente no realizar la acción?
Tu respuesta:
1. Razón: {{Razón}} Respuesta: {{Sí/No/Ambiguo}}2. Razón: {{Razón}} Respuesta: {{Sí/No}}"""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, 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:
@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}}