README.md

---
license: apache-2.0

---

# Multilingual Medicine: Model, Dataset, Benchmark, Code

Covering English, Chinese, French, Hindi, Spanish, Hindi, Arabic So far


<p align="center">
   👨🏻‍💻<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> 
   <br>  <a href="./README_zh.md"> 中文 </a> | <a href="./README.md"> English
</p>


![Apollo](assets/apollo_medium_final.png)

## 🌈 Update

* **[2024.04.28]** We have updated multiple versions of the Apollo-7B GGUF model.
* **[2024.03.07]** [Paper](https://arxiv.org/abs/2403.03640) released.
* **[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！🎉
* **[2024.01.23]** Apollo repo is published！🎉

## Overview

| Type | Size/GB | Notes |
|:-|----:|:----|
| [Q2_K](https://huggingface.co/FreedomIntelligence/Apollo-7B-GGUF/resolve/main/Apollo-7B.Q2_K.gguf) | 3.6 |  |
| [IQ3_XS](https://huggingface.co/FreedomIntelligence/Apollo-7B-GGUF/resolve/main/Apollo-7B.IQ3_XS.gguf) | 3.9 |  |
| [IQ3_S](https://huggingface.co/FreedomIntelligence/Apollo-7B-GGUF/resolve/main/Apollo-7B.IQ3_S.gguf) | 4.1 | beats Q3_K* |
| [Q3_K_S](https://huggingface.co/FreedomIntelligence/Apollo-7B-GGUF/resolve/main/Apollo-7B.Q3_K_S.gguf) | 4.1 |  |
| [IQ3_M](https://huggingface.co/FreedomIntelligence/Apollo-7B-GGUF/resolve/main/Apollo-7B.IQ3_M.gguf)  | 4.2 |  |
| [Q3_K_M](https://huggingface.co/FreedomIntelligence/Apollo-7B-GGUF/resolve/main/Apollo-7B.Q3_K_M.gguf) | 4.5 | lower quality |
| [Q3_K_L](https://huggingface.co/FreedomIntelligence/Apollo-7B-GGUF/resolve/main/Apollo-7B.Q3_K_L.gguf)  | 4.8 |  |
| [IQ4_XS](https://huggingface.co/FreedomIntelligence/Apollo-7B-GGUF/resolve/main/Apollo-7B.IQ4_XS.gguf)  | 4.9 |  |
| [Q4_K_S](https://huggingface.co/FreedomIntelligence/Apollo-7B-GGUF/resolve/main/Apollo-7B.Q4_K_S.gguf) | 5.1 | fast, recommended |
| [Q4_K_M](https://huggingface.co/FreedomIntelligence/Apollo-7B-GGUF/resolve/main/Apollo-7B.Q4_K_M.gguf) | 5.4 | fast, recommended |
| [Q5_K_S](https://huggingface.co/FreedomIntelligence/Apollo-7B-GGUF/resolve/main/Apollo-7B.Q5_K_S.gguf) | 6.1 |  |
| [Q5_K_M](https://huggingface.co/FreedomIntelligence/Apollo-7B-GGUF/resolve/main/Apollo-7B.Q5_K_M.gguf) | 6.2 |  |
| [Q6_K](https://huggingface.co/FreedomIntelligence/Apollo-7B-GGUF/resolve/main/Apollo-7B.Q6_K.gguf) | 7.1 | very good quality |
| [Q8_0](https://huggingface.co/FreedomIntelligence/Apollo-7B-GGUF/resolve/main/Apollo-7B.Q8_0.gguf) | 9.2 | fast, best quality, but very large |
  

## Results

  🤗<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>

   🤗 <a href="https://huggingface.co/FreedomIntelligence/Apollo-0.5B-GGUF" target="_blank">Apollo-0.5B-GGUF</a> • 🤗 <a href="https://huggingface.co/FreedomIntelligence/Apollo-2B-GGUF" target="_blank">Apollo-2B-GGUF</a>  • 🤗 <a href="https://huggingface.co/FreedomIntelligence/Apollo-6B-GGUF" target="_blank">Apollo-6B-GGUF</a> • 🤗 <a href="https://huggingface.co/FreedomIntelligence/Apollo-7B-GGUF" target="_blank">Apollo-7B-GGUF</a>


   ![Apollo](assets/result.png)




## Dataset & Evaluation

- Dataset
  🤗 <a href="https://huggingface.co/datasets/FreedomIntelligence/ApolloCorpus" target="_blank">ApolloCorpus</a>

  <details><summary>Click to expand</summary>


    ![Apollo](assets/dataset.png)

    - [Zip File](https://huggingface.co/datasets/FreedomIntelligence/ApolloCorpus/blob/main/ApolloCorpus.zip)

    - [Data category](https://huggingface.co/datasets/FreedomIntelligence/ApolloCorpus/tree/main/train)

      - Pretrain:

        - data item:

          - 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_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",
                ...
              ],
              ...
            ]
          ```


   </details>



- Evaluation
  🤗 <a href="https://huggingface.co/datasets/FreedomIntelligence/XMedbench" target="_blank">XMedBench</a>

  <details><summary>Click to expand</summary>


     - EN:
       - [MedQA-USMLE](https://huggingface.co/datasets/GBaker/MedQA-USMLE-4-options) 
       - [MedMCQA](https://huggingface.co/datasets/medmcqa/viewer/default/test)
       - [PubMedQA](https://huggingface.co/datasets/pubmed_qa): Because the results fluctuated too much, they were not used in the paper.
       - [MMLU-Medical](https://huggingface.co/datasets/cais/mmlu)
         - Clinical knowledge, Medical genetics, Anatomy, Professional medicine, College biology, College medicine
     - ZH:
       - [MedQA-MCMLE](https://huggingface.co/datasets/bigbio/med_qa/viewer/med_qa_zh_4options_bigbio_qa/test)
       - [CMB-single](https://huggingface.co/datasets/FreedomIntelligence/CMB): Not used in the paper
         - Randomly sample 2,000 multiple-choice questions with single answer.
       - [CMMLU-Medical](https://huggingface.co/datasets/haonan-li/cmmlu)
         - Anatomy, Clinical_knowledge, College_medicine, Genetics, Nutrition, Traditional_chinese_medicine, Virology
       - [CExam](https://github.com/williamliujl/CMExam): Not used in the paper
         - Randomly sample 2,000 multiple-choice questions


     - ES: [Head_qa](https://huggingface.co/datasets/head_qa)
     - FR: [Frenchmedmcqa](https://github.com/qanastek/FrenchMedMCQA)
     - HI: [MMLU_HI](https://huggingface.co/datasets/FreedomIntelligence/MMLU_Arabic)
        - Clinical knowledge, Medical genetics, Anatomy, Professional medicine, College biology, College medicine
     - AR: [MMLU_Ara](https://huggingface.co/datasets/FreedomIntelligence/MMLU_Hindi)
        - Clinical knowledge, Medical genetics, Anatomy, Professional medicine, College biology, College medicine


   </details>


## Results reproduction

   <details><summary>Click to expand</summary>


   **Waiting for Update**
      


   </details>


##  Acknowledgment

We sincerely thank [mradermacher](https://huggingface.co/mradermacher/Apollo-7B-GGUF) for the assistance in providing multiple versions of the Apollo-7B GGUF model!


##  Citation

Please use the following citation if you intend to use our dataset for training or evaluation:

```
@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}
}
```