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  # Democratizing Medical LLMs For Much More Languages
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  Covering 12 Major Languages including English, Chinese, French, Hindi, Spanish, Arabic, Russian, Japanese, Korean, German, Italian, Portuguese and 38 Minor Languages So far.
 
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  <p align="center">
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- 📃 <a href="https://arxiv.org/abs/2410.10626" target="_blank">Paper</a> • 🌐 <a href="" target="_blank">Demo</a> • 🤗 <a href="https://huggingface.co/datasets/FreedomIntelligence/ApolloMoEDataset" target="_blank">ApolloMoEDataset</a> • 🤗 <a href="https://huggingface.co/datasets/FreedomIntelligence/ApolloMoEBench" target="_blank">ApolloMoEBench</a> • 🤗 <a href="https://huggingface.co/collections/FreedomIntelligence/apollomoe-and-apollo2-670ddebe3bb1ba1aebabbf2c" target="_blank">Models</a> • 🌐 <a href="https://github.com/FreedomIntelligence/Apollo" target="_blank">Apollo</a> • 🌐 <a href="https://github.com/FreedomIntelligence/ApolloMoE" target="_blank">ApolloMoE</a>
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  </p>
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  ![Apollo](assets/apollo_medium_final.png)
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  ## 🌈 Update
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  * **[2024.10.15]** ApolloMoE repo is published!🎉
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  ## Architecture
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  <details>
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  ![ApolloMoE](assets/post_moe_results.png)
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  </details>
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  ## Usage Format
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  #### Apollo2
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  #### Apollo-MoE
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  - 0.5B, 1.5B, 7B: User:{query}\nAssistant:{response}<|endoftext|>
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  ## Dataset & Evaluation
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  - Dataset
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  - RU: [RuMedBench](https://github.com/sb-ai-lab/MedBench)
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  </details>
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  <details><summary>Click to expand</summary>
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- We take Gemma-2b as example
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  1. Download Dataset for project:
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  ```
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- bash 0.download_data.sh
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  ```
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- 2. Prepare test and dev for specific model:
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- - Create test data for with special token, you can use ./util/check.ipynb to check models' special tokens
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  ```
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  bash 1.data_process_test&dev.sh
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  4. Train the model
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- - If you want to train in Multi Nodes please refer to ./scripts/multi_node_train_*.sh
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  ```
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- bash 3.single_node_train_gemma.sh
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  ```
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  bash 4.eval.sh
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  ```
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- 6. Evaluate your model: Play with your ckpts in bash
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- ```
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- python ./src/evaluate/cli_demo.py --model_name='./ckpts/your/path/tfmr'
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- ```
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  </details>
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  # Democratizing Medical LLMs For Much More Languages
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  Covering 12 Major Languages including English, Chinese, French, Hindi, Spanish, Arabic, Russian, Japanese, Korean, German, Italian, Portuguese and 38 Minor Languages So far.
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+ <center>
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  <p align="center">
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+ 📃 <a href="https://arxiv.org/abs/2410.10626" target="_blank">Paper</a> • 🌐 <a href="" target="_blank">Demo</a> • 🤗 <a href="https://huggingface.co/datasets/FreedomIntelligence/ApolloMoEDataset" target="_blank">ApolloMoEDataset</a> • 🤗 <a href="https://huggingface.co/datasets/FreedomIntelligence/ApolloMoEBench" target="_blank">ApolloMoEBench</a> • 🤗 <a href="https://huggingface.co/collections/FreedomIntelligence/apollomoe-and-apollo2-670ddebe3bb1ba1aebabbf2c" target="_blank">Models</a> • 🌐 <a href="https://github.com/FreedomIntelligence/Apollo" target="_blank">Apollo</a>
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  </p>
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  ![Apollo](assets/apollo_medium_final.png)
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  ## 🌈 Update
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  * **[2024.10.15]** ApolloMoE repo is published!🎉
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+ ## Languages Coverage
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+ 12 Major Languages and 38 Minor Languages
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+ <details>
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+ <summary>Click to view the Languages Coverage</summary>
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+ ![ApolloMoE](assets/languages.png)
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+ </details>
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  ## Architecture
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  <details>
 
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  ![ApolloMoE](assets/post_moe_results.png)
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  </details>
 
 
 
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  ## Usage Format
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  #### Apollo2
 
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  #### Apollo-MoE
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  - 0.5B, 1.5B, 7B: User:{query}\nAssistant:{response}<|endoftext|>
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  ## Dataset & Evaluation
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  - Dataset
 
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  - RU: [RuMedBench](https://github.com/sb-ai-lab/MedBench)
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  </details>
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  <details><summary>Click to expand</summary>
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+ We take Apollo2-7B or Apollo-MoE-0.5B as example
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  1. Download Dataset for project:
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  ```
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+ bash 0.download_data.sh 
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  ```
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+ 2. Prepare test and dev data for specific model:
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+ - Create test data for with special token
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  ```
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  bash 1.data_process_test&dev.sh
 
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  4. Train the model
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+ - If you want to train in Multi Nodes please refer to ./src/sft/training_config/zero_multi.yaml
 
 
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  ```
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+ bash 3.single_node_train.sh
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  ```
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  bash 4.eval.sh
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  ```
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  </details>
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