--- 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 # - config_name: pretrain_qa # data_files: # - split: medicalBook_en # path: train/pretrain/medicalBook_en_qa.json # - split: medicalBook_zh # path: train/pretrain/medicalBook_zh_qa.json # - split: medicalGuideline_en # path: train/pretrain/medicalGuideline_en_qa.json # - split: medicalPaper_en # path: train/pretrain/medicalPaper_en_qa.json # - split: medicalPaper_es # path: train/pretrain/medicalPaper_es_qa.json # - split: medicalPaper_fr # path: train/pretrain/medicalPaper_fr_qa.json # - split: medicalPaper_zh # path: train/pretrain/medicalPaper_zh_qa.json # - split: medicalWeb_en # path: train/pretrain/medicalWeb_en_qa.json # - split: medicalWeb_es # path: train/pretrain/medicalWeb_es_qa.json # - split: medicalWeb_zh # path: train/pretrain/medicalWeb_zh_qa.json # - split: medicalWiki_en # path: train/pretrain/medicalWiki_en_qa.json # - split: medicalWiki_fr # path: train/pretrain/medicalWiki_fr_qa.json # - split: medicalWiki_hi # path: train/pretrain/medicalWiki_hi_qa.json # - config_name: sft # data_files: # - split: code_en # path: train/sft/code_en.json # - split: code_zh # path: train/sft/code_zh.json # - split: general_ar # path: train/sft/general_ar.json # - split: general_en # path: train/sft/general_en.json # - split: general_es # path: train/sft/general_es.json # - split: general_fr # path: train/sft/general_fr.json # - split: general_hi # path: train/sft/general_hi.json # - split: general_zh # path: train/sft/general_zh.json # - split: math_en # path: train/sft/math_en.json # - split: math_zh # path: train/sft/math_zh.json # - split: medicalExam_en # path: train/sft/medicalExam_en_clean.json # - split: medicalExam_es # path: train/sft/medicalExam_es_clean.json # - split: medicalExam_fr # path: train/sft/medicalExam_fr_clean.json # - split: medicalExam_zh # path: train/sft/medicalExam_zh_clean.json # - split: medicalPatient_ar # path: train/sft/medicalPatient_ar.json # - split: medicalPatient_en # path: train/sft/medicalPatient_en.json # - split: medicalPatient_zh # path: train/sft/medicalPatient_zh.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

![Apollo](assets/apollo_medium_final.png) ## 🌈 Update * **[2024.03.07]** [Paper](https://arxiv.org/abs/2403.03640) 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
Click to expand ![Apollo](assets/result.png)
## Data: Huge, Diverse, Clean, Multilingual ![Apollo](assets/dataset.png) ## Usage - [Zip File](https://huggingface.co/datasets/FreedomIntelligence/Medbase_data/blob/main/Medbase_data-datasets.zip) - [Data category](https://huggingface.co/datasets/FreedomIntelligence/Medbase_data/tree/main/train) - 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", ... ], ... ] ``` - 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", ... ], ... ] ``` ## 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} } ```