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[doc] fixed compatiblity with docusaurus (#2657)

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Frank Lee
2023-02-09 17:06:29 +08:00
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docs/source/en/Colossal-Auto/get_started/run_demo.md
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@@ -9,7 +9,7 @@ Detailed instructions can be found in its `README.md`.
### 2. Integration with activation checkpoint
Colossal-Auto's automatic search function for activation checkpointing finds the most efficient checkpoint within a given memory budget, rather than just aiming for maximum memory compression. To avoid a lengthy search process for an optimal activation checkpoint, Colossal-Auto has implemented a two-stage search process. This allows the system to find a feasible distributed training solution in a reasonable amount of time while still benefiting from activation checkpointing for memory management. The integration of activation checkpointing in Colossal-AI improves the efficiency and effectiveness of large model training. You can follow the [Resnet example](TBA).
Colossal-Auto's automatic search function for activation checkpointing finds the most efficient checkpoint within a given memory budget, rather than just aiming for maximum memory compression. To avoid a lengthy search process for an optimal activation checkpoint, Colossal-Auto has implemented a two-stage search process. This allows the system to find a feasible distributed training solution in a reasonable amount of time while still benefiting from activation checkpointing for memory management. The integration of activation checkpointing in Colossal-AI improves the efficiency and effectiveness of large model training. You can follow the [Resnet example](https://github.com/hpcaitech/ColossalAI/tree/main/examples/tutorial/auto_parallel).
Detailed instructions can be found in its `README.md`.
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