File size: 7,223 Bytes
7d586e4 3849321 1887785 5068040 7d586e4 16cef02 07de217 f6702a9 16cef02 07de217 16cef02 07de217 189ae33 16cef02 07de217 16cef02 dd2d938 9cc6fe5 21353f7 16cef02 21353f7 07de217 dd2d938 ed3c4bb 07de217 38f53e9 07de217 16cef02 07de217 |
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 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 |
---
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
<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
* **[2024.03.07]** [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!🎉
## 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>
<details><summary>Click to expand</summary>
![Apollo](assets/result.png)
</details>
## 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}
}
``` |