metadata
license: apache-2.0
configs:
- config_name: pretrain_text
data_files:
- split: medicalBook_en
path: train/pretrain/medicalBook_en_text.json
- split: medicalBook_zh
path: train/pretrain/medicalBook_zh_text.json
- split: medicalGuideline_en
path: train/pretrain/medicalGuideline_en_text.json
- split: medicalPaper_en
path: train/pretrain/medicalPaper_en_text.json
- split: medicalPaper_es
path: train/pretrain/medicalPaper_es_text.json
- split: medicalPaper_fr
path: train/pretrain/medicalPaper_fr_text.json
- split: medicalPaper_zh
path: train/pretrain/medicalPaper_zh_text.json
- split: medicalWeb_en
path: train/pretrain/medicalWeb_en_text.json
- split: medicalWeb_es
path: train/pretrain/medicalWeb_es_text.json
- split: medicalWeb_zh
path: train/pretrain/medicalWeb_zh_text.json
- split: medicalWiki_en
path: train/pretrain/medicalWiki_en_text.json
- split: medicalWiki_fr
path: train/pretrain/medicalWiki_fr_text.json
- split: medicalWiki_hi
path: train/pretrain/medicalWiki_hi_text.json
Multilingual Medicine: Model, Dataset, Benchmark, Code
Covering English, Chinese, French, Hindi, Spanish, Hindi, Arabic So far
👨🏻💻Github •📃 Paper • 🌐 Demo • 🤗 ApolloCorpus • 🤗 XMedBench
中文 | English
🌈 Update
- [2024.03.07] Paper released.
- [2024.02.12] ApolloCorpus and XMedBench is published!🎉
- [2024.01.23] Apollo repo is published!🎉
Results
Apollo-0.5B • 🤗 Apollo-1.8B • 🤗 Apollo-2B • 🤗 Apollo-6B • 🤗 Apollo-7B
Data: Huge, Diverse, Clean, Multilingual
Usage
- Zip File
- Data category
Pretrain:
- json_name: {data_source}_{language}_{data_type}.json
- data_type: medicalBook, medicalGuideline, medicalPaper, medicalWeb(from online forum), medicalWiki
- language: en(English), zh(chinese), es(spanish), fr(french), hi(Hindi)
- data_type: qa(generated qa from text)
- data item:
- data_type==text: list of string
[ "string1", "string2", ... ]
- data_type==qa: list of qa pairs(list of string)
[ [ "q1", "a1", "q2", "a2", ... ], ... ]
- data_type==text: list of string
- json_name: {data_source}_{language}_{data_type}.json
SFT:
- json_name: {data_source}_{language}.json
- data_type: code, general, math, medicalExam, medicalPatient
- data item: list of qa pairs(list of string)
[ [ "q1", "a1", "q2", "a2", ... ], ... ]
- json_name: {data_source}_{language}.json
Citation
@misc{wang2024apollo,
title={Apollo: Lightweight Multilingual Medical LLMs towards Democratizing Medical AI to 6B People},
author={Xidong Wang and Nuo Chen and Junyin Chen and Yan Hu and Yidong Wang and Xiangbo Wu and Anningzhe Gao and Xiang Wan and Haizhou Li and Benyou Wang},
year={2024},
eprint={2403.03640},
archivePrefix={arXiv},
primaryClass={cs.CL}
}