Harmony Clinical Structuring QLoRA Adapter
This repository contains a proof-of-concept QLoRA adapter for structured clinical information extraction.
Base model
Qwen/Qwen2.5-3B-Instruct
Task
The model takes clinical text as input and returns schema-valid JSON containing extracted:
- medications
- adverse events
- dosage attributes where available
- linked medication information
- evidence text
- source spans
Training setup
- Method: QLoRA
- Quantization: 4-bit NF4
- LoRA rank: 16
- LoRA alpha: 32
- LoRA dropout: 0.05
- Training steps: 200
- Dataset: ADE Corpus v2
- Frameworks: Hugging Face Transformers, PEFT, TRL, PyTorch
Intended project use
In the Harmony Healthcare RAG workflow, this adapter is intended to run at ingestion time after OCR and chunking. It enriches text chunks with structured medication and adverse-event metadata for SQLite storage, search filtering, review, and UI display.
Status
This is a project/demo proof-of-concept adapter, not a production clinical model.
Limitations
- Not clinically validated
- Not for diagnosis or treatment decisions
- Not production-ready
- Longer chunked training is recommended for stronger span accuracy
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