Apollo: Lightweight Multilingual Medical LLMs towards Democratizing Medical AI to 6B People
Paper
β’
2403.03640
β’
Published
β’
2
Covering English, Chinese, French, Hindi, Spanish, Hindi, Arabic So far
π¨π»βπ»Github β’π Paper β’ π Demo β’ π€ ApolloCorpus β’ π€ XMedBench
δΈζ | English
π€Apollo-0.5B β’ π€ Apollo-1.8B β’ π€ Apollo-2B β’ π€ Apollo-6B β’ π€ Apollo-7B π€ Apollo-34B β’ π€ Apollo-72B
π€ Apollo-0.5B-GGUF β’ π€ Apollo-2B-GGUF β’ π€ Apollo-6B-GGUF β’ π€ Apollo-7B-GGUF
Dataset π€ ApolloCorpus
[
"string1",
"string2",
...
]
[
[
"q1",
"a1",
"q2",
"a2",
...
],
...
]
[
[
"q1",
"a1",
"q2",
"a2",
...
],
...
]
Evaluation π€ XMedBench
EN:
ZH:
ES: Head_qa
FR: Frenchmedmcqa
HI: MMLU_HI
AR: MMLU_Ara
Waiting for Update
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}
}
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