You can deploy this model and start earning money today!

FreedomIntelligence/
Apollo-MedJamba

Name: Apollo-MedJamba
Rating: 2.5 (49 reviews)

Views

No views yet

MedJamba

Multilingual Medical Model Based On Jamba

👨🏻‍💻Github •📃 Paper

🌈 Update

[2024.04.25] MedJamba Model is published！🎉

Results

🤗 Apollo-0.5B • 🤗 Apollo-1.8B • 🤗 Apollo-2B • 🤗 Apollo-6B • 🤗 Apollo-7B • 🤗 Apollo-34B • 🤗 Apollo-72B

🤗 MedJamba

🤗 Apollo-0.5B-GGUF • 🤗 Apollo-2B-GGUF • 🤗 Apollo-6B-GGUF • 🤗 Apollo-7B-GGUF

Dataset & Evaluation

Dataset 🤗 ApolloCorpus
Click to expand

Apollo
- Zip File
- Data category
  - 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", ... ], ... ]
Evaluation 🤗 XMedBench
Click to expand
- EN:
  - MedQA-USMLE
  - MedMCQA
  - PubMedQA: Because the results fluctuated too much, they were not used in the paper.
  - MMLU-Medical
    - Clinical knowledge, Medical genetics, Anatomy, Professional medicine, College biology, College medicine
- ZH:
  - MedQA-MCMLE
  - CMB-single: Not used in the paper
    - Randomly sample 2,000 multiple-choice questions with single answer.
  - CMMLU-Medical
    - Anatomy, Clinical_knowledge, College_medicine, Genetics, Nutrition, Traditional_chinese_medicine, Virology
  - CExam: Not used in the paper
    - Randomly sample 2,000 multiple-choice questions
- ES: Head_qa
- FR: Frenchmedmcqa
- HI: MMLU_HI
  - Clinical knowledge, Medical genetics, Anatomy, Professional medicine, College biology, College medicine
- AR: MMLU_Ara
  - Clinical knowledge, Medical genetics, Anatomy, Professional medicine, College biology, College medicine

Results reproduction

Click to expand

Download Dataset for project:

bash 0.download_data.sh
Prepare test and dev for specific model:
- Create test data for with special token, you can use ./util/check.ipynb to check models' special tokens
bash 1.data_process_test&dev.sh
Prepare train data for specific model (Create tokenized data in advance):
- You can adjust data Training order and Training Epoch in this step
bash 2.data_process_train.sh
Train the model
- Multi Nodes refer to ./scripts/multi_node_train_*.sh
```
pip install causal-conv1d>=1.2.0
pip install mamba-ssm
```
Node 0:

bash ./scripts/3.multinode_train_jamba_rank0.sh

... Node 4:

bash ./scripts/3.multinode_train_jamba_rank4.sh
Evaluate your model: Generate score for benchmark

bash 4.eval.sh
Evaluate your model: Play with your ckpts in bash

python ./src/evaluate/cli_demo.py --model_name='./ckpts/your/path/tfmr'

To do

Long Context Capability Evaluation and new Long-Med Benchmark

Acknowledgment

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}
}

FreedomIntelligence/Apollo-MedJamba