83 lines
2.6 KiB
Markdown
83 lines
2.6 KiB
Markdown
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---
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library_name: transformers
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tags:
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- reasoning
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- text-generation
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- medical-ai
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- multilingual-ai
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- healthcare
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- LLMs
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license: apache-2.0
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datasets:
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- Aikyam-Lab/CUREMED-BENCH
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language:
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- am
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- bn
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- fr
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- ha
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- hi
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- ja
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- ko
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- es
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- sw
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- th
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- tr
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- vi
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- yo
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base_model:
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- Qwen/Qwen2.5-3B-Instruct
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pipeline_tag: text-generation
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---
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# Model Card for Model ID
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CURE-MED-1.5B is a 1.5 billion parameter large language model specialized for multilingual medical reasoning, fine-tuned from Qwen/Qwen1.5-1.5B-instruct using a
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curriculum-informed reinforcement learning framework to enhance logical correctness and language stability in healthcare applications.
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## Model Details
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CURE-MED-1.5B is part of the CURE-MED family of models, designed to address the challenges of multilingual medical reasoning in large language models (LLMs).
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Built on the Qwen2.5-1.5B-instruct model, it incorporates a curriculum-informed reinforcement learning approach that integrates code-switching-aware supervised fine-tuning (SFT)
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and Group Relative Policy Optimization (GRPO) to improve performance on open-ended medical queries across 13 languages, including underrepresented ones such as Amharic, Yoruba, and Swahili.
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The model is trained and evaluated using CUREMED-BENCH, a high-quality multilingual open-ended medical reasoning benchmark with single verifiable answers.
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### Model Description
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<!-- Provide a longer summary of what this model is. -->
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This is the model card of a 🤗 transformers model that has been pushed on the Hub.
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- **Developed by:** Eric Onyame, Akash Ghosh, Subhadip Baidya, Sriparna Saha, Xiuying Chen, Chirag Agarwal (Aikyam Lab and collaborators)
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- **Shared by:** Aikyam Lab
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- **Model type:** Multilingual medical reasoning large language model
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- **Language(s) (NLP):** Amharic, Bengali, French, Hausa, Hindi, Japanese, Korean, Spanish, Swahili, Thai, Turkish, Vietnamese, Yoruba
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- **License:** Apache 2.0
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- **Finetuned from model:** Qwen2.5-Instruct (1.5B, 3B, 7B, 14B, 32B variants)
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### Model Sources
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- **Repository:** https://github.com/AikyamLab/cure-med
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- **Paper:** https://arxiv.org/abs/2601.13262
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- **Demo:** https://cure-med.github.io/
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## Citation
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**BibTeX:**
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```bibtex
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@article{onyame2026cure,
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title={CURE-Med: Curriculum-Informed Reinforcement Learning for Multilingual Medical Reasoning},
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author={Onyame, Eric and Ghosh, Akash and Baidya, Subhadip and Saha, Sriparna and Chen, Xiuying and Agarwal, Chirag},
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journal={arXiv preprint arXiv:2601.13262},
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year={2026}
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}
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