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README.md
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---
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license: apache-2.0
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---
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---
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pipeline_tag: text-generation
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language: multilingual
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license: apache-2.0
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tags:
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- "Multitask Language Understanding"
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- "Multilingual"
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widget:
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- text: "In traditional Western medicine, which vitamin is commonly recommended to prevent scurvy? A) Vitamin A B) Vitamin B12 C) Vitamin C D) Vitamin D"
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example_title: "English"
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- text: "在中医理论中,以下哪种药材不是治疗风湿病的常用药物? A) 独活 B) 秦艽 C) 甘草 D) 珍珠粉"
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example_title: "Chinese"
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- text: "السؤال:** ما هو العلاج الطبيعي الذي يستخدم تقليديًا في الطب العربي لتحسين الهضم؟ A) الزنجبيل B) النعناع C) القرفة D) الحلبة"
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example_title: "Arabic"
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- text: "आयुर्वेद में, किस औषधि का उपयोग आमतौर पर जुकाम के इलाज के लिए किया जाता है? A) नीम B) तुलसी C) गिलोय D) अश्वगंधा"
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example_title: "Hindi"
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- text: "En la medicina tradicional española, ¿qué alimento se considera beneficioso para la salud del hígado? A) Aceite de oliva B) Tomate C) Foie gras (hígado de ganso) D) Ajo"
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example_title: "Spanish"
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- text: "Dans la tradition médicinale française, quel produit est réputé pour ses bienfaits sur la digestion ? A) Le vin rouge B) Le fromage C) Le foie gras D) Les herbes de Provence"
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example_title: "French"
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---
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# Multilingual Medicine: Model, Dataset, Benchmark, Code
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Covering English, Chinese, French, Hindi, Spanish, Hindi, Arabic So far
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<p align="center">
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👨🏻💻<a href="https://github.com/FreedomIntelligence/Apollo" target="_blank">Github</a> •📃 <a href="https://arxiv.org/abs/2403.03640" target="_blank">Paper</a> • 🌐 <a href="https://apollo.llmzoo.com/" target="_blank">Demo</a> • 🤗 <a href="https://huggingface.co/datasets/FreedomIntelligence/ApolloCorpus" target="_blank">ApolloCorpus</a> • 🤗 <a href="https://huggingface.co/datasets/FreedomIntelligence/XMedbench" target="_blank">XMedBench</a>
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<br> <a href="./README_zh.md"> 中文 </a> | <a href="./README.md"> English
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</p>
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![Apollo](assets/apollo_medium_final.png)
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## 🌈 Update
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* **[2024.03.07]** [Paper](https://arxiv.org/abs/2403.03640) released.
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* **[2024.02.12]** <a href="https://huggingface.co/datasets/FreedomIntelligence/ApolloCorpus" target="_blank">ApolloCorpus</a> and <a href="https://huggingface.co/datasets/FreedomIntelligence/XMedbench" target="_blank">XMedBench</a> is published!🎉
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* **[2024.01.23]** Apollo repo is published!🎉
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## Results
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<a href="https://huggingface.co/FreedomIntelligence/Apollo-0.5B" target="_blank">Apollo-0.5B</a> • 🤗 <a href="https://huggingface.co/FreedomIntelligence/Apollo-1.8B" target="_blank">Apollo-1.8B</a> • 🤗 <a href="https://huggingface.co/FreedomIntelligence/Apollo-2B" target="_blank">Apollo-2B</a> • 🤗 <a href="https://huggingface.co/FreedomIntelligence/Apollo-6B" target="_blank">Apollo-6B</a> • 🤗 <a href="https://huggingface.co/FreedomIntelligence/Apollo-7B" target="_blank">Apollo-7B</a>
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![Apollo](assets/result.png)
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## Dataset & Evaluation
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- Dataset
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🤗 <a href="https://huggingface.co/datasets/FreedomIntelligence/ApolloCorpus" target="_blank">ApolloCorpus</a>
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<details><summary>Click to expand</summary>
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![Apollo](assets/dataset.png)
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- [Zip File](https://huggingface.co/datasets/FreedomIntelligence/ApolloCorpus/blob/main/ApolloCorpus.zip)
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- [Data category](https://huggingface.co/datasets/FreedomIntelligence/ApolloCorpus/tree/main/train)
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- Pretrain:
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- data item:
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- json_name: {data_source}_{language}_{data_type}.json
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- data_type: medicalBook, medicalGuideline, medicalPaper, medicalWeb(from online forum), medicalWiki
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- language: en(English), zh(chinese), es(spanish), fr(french), hi(Hindi)
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- data_type: qa(generated qa from text)
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- data_type==text: list of string
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```
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[
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"string1",
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"string2",
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...
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]
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```
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- data_type==qa: list of qa pairs(list of string)
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```
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[
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[
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"q1",
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"a1",
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"q2",
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"a2",
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...
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],
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...
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]
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```
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- SFT:
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- json_name: {data_source}_{language}.json
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- data_type: code, general, math, medicalExam, medicalPatient
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- data item: list of qa pairs(list of string)
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```
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[
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[
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"q1",
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"a1",
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"q2",
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"a2",
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...
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],
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...
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]
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```
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</details>
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- Evaluation
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🤗 <a href="https://huggingface.co/datasets/FreedomIntelligence/XMedbench" target="_blank">XMedBench</a>
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<details><summary>Click to expand</summary>
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- EN:
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- [MedQA-USMLE](https://huggingface.co/datasets/GBaker/MedQA-USMLE-4-options)
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- [MedMCQA](https://huggingface.co/datasets/medmcqa/viewer/default/test)
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- [PubMedQA](https://huggingface.co/datasets/pubmed_qa): Because the results fluctuated too much, they were not used in the paper.
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- [MMLU-Medical](https://huggingface.co/datasets/cais/mmlu)
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- Clinical knowledge, Medical genetics, Anatomy, Professional medicine, College biology, College medicine
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- ZH:
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- [MedQA-MCMLE](https://huggingface.co/datasets/bigbio/med_qa/viewer/med_qa_zh_4options_bigbio_qa/test)
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- [CMB-single](https://huggingface.co/datasets/FreedomIntelligence/CMB): Not used in the paper
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- Randomly sample 2,000 multiple-choice questions with single answer.
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- [CMMLU-Medical](https://huggingface.co/datasets/haonan-li/cmmlu)
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- Anatomy, Clinical_knowledge, College_medicine, Genetics, Nutrition, Traditional_chinese_medicine, Virology
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- [CExam](https://github.com/williamliujl/CMExam): Not used in the paper
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- Randomly sample 2,000 multiple-choice questions
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- ES: [Head_qa](https://huggingface.co/datasets/head_qa)
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- FR: [Frenchmedmcqa](https://github.com/qanastek/FrenchMedMCQA)
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- HI: [MMLU_HI](https://huggingface.co/datasets/FreedomIntelligence/MMLU_Arabic)
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- Clinical knowledge, Medical genetics, Anatomy, Professional medicine, College biology, College medicine
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- AR: [MMLU_Ara](https://huggingface.co/datasets/FreedomIntelligence/MMLU_Hindi)
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- Clinical knowledge, Medical genetics, Anatomy, Professional medicine, College biology, College medicine
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</details>
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## Results reproduction
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<details><summary>Click to expand</summary>
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**Waiting for Update**
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</details>
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## Citation
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Please use the following citation if you intend to use our dataset for training or evaluation:
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```
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@misc{wang2024apollo,
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title={Apollo: Lightweight Multilingual Medical LLMs towards Democratizing Medical AI to 6B People},
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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},
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year={2024},
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eprint={2403.03640},
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archivePrefix={arXiv},
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primaryClass={cs.CL}
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}
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```
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