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@@ -76,12 +76,23 @@ Covering 12 Major Languages including English, Chinese, French, Hindi, Spanish,
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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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  <summary>Click to view the MoE routing image</summary>
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- ![ApolloMoE](/assets/hybrid_routing.png)
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  </details>
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@@ -188,17 +199,17 @@ Covering 12 Major Languages including English, Chinese, French, Hindi, Spanish,
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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
@@ -206,23 +217,21 @@ Covering 12 Major Languages including English, Chinese, French, Hindi, Spanish,
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  3. Prepare train data for specific model (Create tokenized data in advance):
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-
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- - 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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-
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  4. Train the model
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-
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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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-
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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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- ```
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- python ./src/evaluate/cli_demo.py --model_name='./ckpts/your/path/tfmr'
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- ```
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-
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  </details>
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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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+
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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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+
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+ </details>
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+
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+
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  ## Architecture
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  <details>
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  <summary>Click to view the MoE routing image</summary>
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+ ![ApolloMoE](assets/hybrid_routing.png)
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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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  3. Prepare train data for specific model (Create tokenized data in advance):
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+ - You can adjust data Training order and Training Epoch in this step
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+
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  ```
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  bash 2.data_process_train.sh
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  ```
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+
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  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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  </details>
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