A QLoRA adapter for Gemma 4 E4B, representing the first iteration of a research initiative to build offline-capable, locally-running LLMs for pediatric clinical decision support in resource-constrained clinical environments.
🤗 Model weights and adapter files are hosted on Hugging Face.
Important
This is the first iteration of the project. Its sole purpose is to validate that the training pipeline, architecture, and hyperparameter configuration are stable and ready for scaled training.
This is NOT a medical device. It has not been validated for clinical use. It has not been benchmarked for diagnostic accuracy. Do not use in any patient-facing context. All outputs must be reviewed by a qualified healthcare professional. The authors accept no liability for decisions made based on model outputs.
| Document | Audience | Contents |
|---|---|---|
README.md |
Everyone | This file — project identity, status, and navigation |
TECHNICAL.md |
Developers | Dataset, architecture, training results, usage, roadmap |
BACKGROUND.md |
Clinical & institutional reviewers | Project vision, SDG alignment, international context, full references |
Released under the Apache 2.0 License, subject to the terms of the Gemma 4 base model license.
- Unsloth — for the fine-tuning framework and Unsloth Studio
- MedMCQA — for the open medical QA dataset
- Google DeepMind — for the Gemma 4 model family
For questions, collaboration proposals, or clinical partnership enquiries, please open an issue in this repository or reach out via the contact details on the author's profile page.