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aerovane0
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Model Details
Model Provider
aerovane0
Model Tree
Qwen/Qwen3-8B
Input Modalities
Output Modalities
Supported Functionality
Public health reasoning requires population-level inference grounded in scientific evidence, expert consensus, and safety constraints. This model addresses the scarcity of supervised signals in this domain. It was trained on the GlobalHealthAtlas dataset, a large-scale multilingual corpus of 280,210 instances spanning 15 domains including infectious disease prevention, health policy, and vaccination.
This model is intended to be used as a question-answering and information retrieval component for research and public health queries.
Important Disclaimer: This model is NOT intended for clinical diagnosis, medical advice, or other high‑stakes decision-making without human review by domain experts.
The model was fine-tuned using LoRA (Low-Rank Adaptation) on the Qwen3-8B base model via the LLaMA Factory framework.
The following hyperparameters were used during training:
If you use this model or the GlobalHealthAtlas dataset, please cite:
bibtex
@article{globalhealthatlas2026,title={From Knowledge to Inference: Formalizing Specialized Public Health Reasoning on GlobalHealthAtlas},author={GlobalHealthAtlas Team},year={2026}}