Spaces:
Running
Running
File size: 1,003 Bytes
d89a8a4 7c0779f d89a8a4 f90ff39 7c0779f 88d77a1 b20f71f 88d77a1 b20f71f 7c0779f 88d77a1 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 | ---
title: README
emoji: 👁
colorFrom: purple
colorTo: gray
sdk: static
pinned: false
---
# 🩹 MedInjection-FR
A **French biomedical instruction dataset and model suite** for studying how data provenance (**native, synthetic, translated**) impacts instruction-tuning of LLMs.
## 📊 Dataset Stats
**Total size**: 571,436 instruction–response pairs
**Components**:
- Native: 77,247
- Synthetic: 76,506
- Translated: 417,674
**Tasks**:
- MCQU (single-answer)
- MCQ (multi-answer)
- OEQ (open-ended)
## Paper
```bibtex
@misc{belmadani2026medinjectionfrexploringrolenative,
title={MedInjection-FR: Exploring the Role of Native, Synthetic, and Translated Data in Biomedical Instruction Tuning},
author={Ikram Belmadani and Oumaima El Khettari and Pacôme Constant dit Beaufils and Benoit Favre and Richard Dufour},
year={2026},
eprint={2603.06905},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2603.06905},
}
```
***
|