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@@ -55,34 +55,24 @@ pipeline_tag: question-answering
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  tags:
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  - biology
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  - medical
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- ---
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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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- ๐Ÿ“ƒ <a href="https://arxiv.org/abs/2410.10626" target="_blank">Paper</a> โ€ข ๐ŸŒ <a href="" target="_blank">Demo</a> โ€ข ๐Ÿค— <a href="https://huggingface.co/datasets/FreedomIntelligence/ApolloMoEDataset" target="_blank">ApolloMoEDataset</a> โ€ข ๐Ÿค— <a href="https://huggingface.co/datasets/FreedomIntelligence/ApolloMoEBench" target="_blank">ApolloMoEBench</a> โ€ข ๐Ÿค— <a href="https://huggingface.co/collections/FreedomIntelligence/apollomoe-and-apollo2-670ddebe3bb1ba1aebabbf2c" target="_blank">Models</a> โ€ข ๐ŸŒ <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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- ## ๐ŸŒˆ Update
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-
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- * **[2024.10.15]** ApolloMoE repo is published๏ผ๐ŸŽ‰
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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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-
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- ![ApolloMoE](assets/languages.png)
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- </details>
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  ## Architecture
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  ### Dense
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  ๐Ÿค— <a href="https://huggingface.co/FreedomIntelligence/Apollo2-0.5B" target="_blank">Apollo2-0.5B</a> โ€ข ๐Ÿค— <a href="https://huggingface.co/FreedomIntelligence/Apollo2-1.5B" target="_blank">Apollo2-1.5B</a> โ€ข ๐Ÿค— <a href="https://huggingface.co/FreedomIntelligence/Apollo2-2B" target="_blank">Apollo2-2B</a> โ€ข ๐Ÿค— <a href="https://huggingface.co/FreedomIntelligence/Apollo2-3.8B" target="_blank">Apollo2-3.8B</a> โ€ข ๐Ÿค— <a href="https://huggingface.co/FreedomIntelligence/Apollo2-7B" target="_blank">Apollo2-7B</a> โ€ข ๐Ÿค— <a href="https://huggingface.co/FreedomIntelligence/Apollo2-9B" target="_blank">Apollo2-9B</a>
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-
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  <details>
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  <summary>Click to view the Dense Models Results</summary>
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-
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  ![ApolloMoE](assets/dense_results.png)
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  </details>
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  ### Post-MoE
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  ๐Ÿค— <a href="https://huggingface.co/FreedomIntelligence/Apollo-MoE-0.5B" target="_blank">Apollo-MoE-0.5B</a> โ€ข ๐Ÿค— <a href="https://huggingface.co/FreedomIntelligence/Apollo-MoE-1.5B" target="_blank">Apollo-MoE-1.5B</a> โ€ข ๐Ÿค— <a href="https://huggingface.co/FreedomIntelligence/Apollo-MoE-7B" target="_blank">Apollo-MoE-7B</a>
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-
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  <details>
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  <summary>Click to view the Post-MoE Models Results</summary>
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-
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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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-
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  ## Dataset & Evaluation
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  - Dataset
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141
  </details>
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-
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  - Evaluation
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  ๐Ÿค— <a href="https://huggingface.co/datasets/FreedomIntelligence/ApolloMoEBench" target="_blank">ApolloMoEBench</a>
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146
  <details><summary>Click to expand</summary>
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-
148
  - EN:
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  - [MedQA-USMLE](https://huggingface.co/datasets/GBaker/MedQA-USMLE-4-options)
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  - [MedMCQA](https://huggingface.co/datasets/medmcqa/viewer/default/test)
@@ -180,25 +175,29 @@ Covering 12 Major Languages including English, Chinese, French, Hindi, Spanish,
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  - PT: [BioInstructQA](https://huggingface.co/datasets/BioMistral/BioInstructQA): Portuguese part
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  - RU: [RuMedBench](https://github.com/sb-ai-lab/MedBench)
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-
 
 
 
 
184
  </details>
185
 
186
-
187
  ## Results reproduction
188
  <details><summary>Click to expand</summary>
189
 
190
-
191
- We take Apollo2-7B or Apollo-MoE-0.5B as example
192
  1. Download Dataset for project:
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194
  ```
195
- bash 0.download_data.shย 
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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
@@ -206,21 +205,23 @@ Covering 12 Major Languages including English, Chinese, French, Hindi, Spanish,
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207
  3. Prepare train data for specific model (Create tokenized data in advance):
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-
210
- - You can adjust data Training order and Training Epoch in this step
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  ```
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  bash 2.data_process_train.sh
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  ```
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-
216
  4. Train the model
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-
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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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233
  </details>
234
 
235
 
 
55
  tags:
56
  - biology
57
  - medical
 
58
  # Democratizing Medical LLMs For Much More Languages
59
 
60
  Covering 12 Major Languages including English, Chinese, French, Hindi, Spanish, Arabic, Russian, Japanese, Korean, German, Italian, Portuguese and 38 Minor Languages So far.
 
61
 
62
 
63
 
64
  <p align="center">
65
+ ๐Ÿ“ƒ <a href="https://arxiv.org/abs/2410.10626" target="_blank">Paper</a> โ€ข ๐ŸŒ <a href="" target="_blank">Demo</a> โ€ข ๐Ÿค— <a href="https://huggingface.co/datasets/FreedomIntelligence/ApolloMoEDataset" target="_blank">ApolloMoEDataset</a> โ€ข ๐Ÿค— <a href="https://huggingface.co/datasets/FreedomIntelligence/ApolloMoEBench" target="_blank">ApolloMoEBench</a> โ€ข ๐Ÿค— <a href="https://huggingface.co/collections/FreedomIntelligence/apollomoe-and-apollo2-670ddebe3bb1ba1aebabbf2c" target="_blank">Models</a> โ€ข ๐ŸŒ <a href="https://github.com/FreedomIntelligence/Apollo" target="_blank">Apollo</a> โ€ข ๐ŸŒ <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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+ ## ๐ŸŒˆ Update
 
 
 
74
 
75
+ * **[2024.10.15]** ApolloMoE repo is published๏ผ๐ŸŽ‰
76
 
77
 
78
  ## Architecture
 
88
 
89
  ### Dense
90
  ๐Ÿค— <a href="https://huggingface.co/FreedomIntelligence/Apollo2-0.5B" target="_blank">Apollo2-0.5B</a> โ€ข ๐Ÿค— <a href="https://huggingface.co/FreedomIntelligence/Apollo2-1.5B" target="_blank">Apollo2-1.5B</a> โ€ข ๐Ÿค— <a href="https://huggingface.co/FreedomIntelligence/Apollo2-2B" target="_blank">Apollo2-2B</a> โ€ข ๐Ÿค— <a href="https://huggingface.co/FreedomIntelligence/Apollo2-3.8B" target="_blank">Apollo2-3.8B</a> โ€ข ๐Ÿค— <a href="https://huggingface.co/FreedomIntelligence/Apollo2-7B" target="_blank">Apollo2-7B</a> โ€ข ๐Ÿค— <a href="https://huggingface.co/FreedomIntelligence/Apollo2-9B" target="_blank">Apollo2-9B</a>
91
+
92
  <details>
93
  <summary>Click to view the Dense Models Results</summary>
94
+
95
  ![ApolloMoE](assets/dense_results.png)
96
 
97
  </details>
98
 
99
  ### Post-MoE
100
  ๐Ÿค— <a href="https://huggingface.co/FreedomIntelligence/Apollo-MoE-0.5B" target="_blank">Apollo-MoE-0.5B</a> โ€ข ๐Ÿค— <a href="https://huggingface.co/FreedomIntelligence/Apollo-MoE-1.5B" target="_blank">Apollo-MoE-1.5B</a> โ€ข ๐Ÿค— <a href="https://huggingface.co/FreedomIntelligence/Apollo-MoE-7B" target="_blank">Apollo-MoE-7B</a>
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+
102
  <details>
103
  <summary>Click to view the Post-MoE Models Results</summary>
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+
105
  ![ApolloMoE](assets/post_moe_results.png)
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107
  </details>
108
 
109
+
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+
111
+
112
+ โ€‹
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+
114
 
115
  ## Usage Format
116
  #### Apollo2
 
120
 
121
  #### Apollo-MoE
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  - 0.5B, 1.5B, 7B: User:{query}\nAssistant:{response}<|endoftext|>
123
+
124
  ## Dataset & Evaluation
125
 
126
  - Dataset
 
134
 
135
 
136
  </details>
137
+
138
  - Evaluation
139
  ๐Ÿค— <a href="https://huggingface.co/datasets/FreedomIntelligence/ApolloMoEBench" target="_blank">ApolloMoEBench</a>
140
 
141
  <details><summary>Click to expand</summary>
142
+
143
  - EN:
144
  - [MedQA-USMLE](https://huggingface.co/datasets/GBaker/MedQA-USMLE-4-options)
145
  - [MedMCQA](https://huggingface.co/datasets/medmcqa/viewer/default/test)
 
175
  - PT: [BioInstructQA](https://huggingface.co/datasets/BioMistral/BioInstructQA): Portuguese part
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  - RU: [RuMedBench](https://github.com/sb-ai-lab/MedBench)
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178
+
179
+ โ€‹
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+ โ€‹
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+
182
+
183
  </details>
184
 
185
+
186
  ## Results reproduction
187
  <details><summary>Click to expand</summary>
188
 
189
+
190
+ We take Gemma-2b as example
191
  1. Download Dataset for project:
192
 
193
  ```
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+ bash 0.download_data.sh
195
  ```
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197
+ 2. Prepare test and dev for specific model:
198
 
199
 
200
+ - Create test data for with special token, you can use ./util/check.ipynb to check models' special tokens
201
 
202
  ```
203
  bash 1.data_process_test&dev.sh
 
205
 
206
  3. Prepare train data for specific model (Create tokenized data in advance):
207
 
 
 
208
 
209
+ - You can adjust data Training order and Training Epoch in this step
210
+
211
  ```
212
  bash 2.data_process_train.sh
213
  ```
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+
215
  4. Train the model
216
 
217
+
218
+ - If you want to train in Multi Nodes please refer to ./scripts/multi_node_train_*.sh
219
+
220
+
221
 
222
 
223
  ```
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+ bash 3.single_node_train_gemma.sh
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  ```
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231
  bash 4.eval.sh
232
  ```
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+ 6. Evaluate your model: Play with your ckpts in bash
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+
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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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+
240
  </details>
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