README.md

---
title: "GLiNER-BioMed PICO Extractor"
emoji: 🧠
colorFrom: gray


colorTo: blue
sdk: gradio
sdk_version: "4.0.0"
app_file: app.py
pinned: false
---
# GLiNER-BioMed PICO Extractor

This Hugging Face Space extracts PICO elements (Population, Intervention, Comparison, Outcome) from:

- Raw biomedical abstracts
- `.nbib` reference files

### Model

Powered by `Ihor/gliner-biomed-bi-small-v1.0` — a compact BERT-like NER model trained for biomedical text using synthetic annotations.

### Features

- ✅ Zero-shot extraction using natural language entity descriptions
- 📄 NBIB parser for PubMed export files
- ⚡ Lightweight: deploys on CPU-only Spaces

### How to Use

1. **Paste a biomedical abstract** in the textbox → Get labeled PICO entities.
2. **Upload a `.nbib` file** → Get per-abstract PICO extractions.

### Dependencies

- `gradio`
- `gliner`
- `torch`
- `transformers`

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Inspired by the needs of evidence-based medicine and large-scale systematic reviews.