[WIP] refactor template

[Jintao-Huang]

No description provided.

[gemini-code-assist]

Summary of Changes

Hello @Jintao-Huang, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request refines the documentation for the liger_kernel feature by adding a specific clarification regarding its current compatibility. The update informs users that the liger_kernel is presently limited to causal_lm task types, ensuring that developers have accurate information when configuring their training setups and avoiding potential issues with unsupported task types.

Highlights

• Documentation Update: Updated both Chinese and English documentation for the liger_kernel parameter.
• Liger Kernel Limitation Clarification: Added a crucial note indicating that liger_kernel currently only supports task_type='causal_lm'.

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[gemini-code-assist]

Code Review

This pull request updates the documentation for the use_liger_kernel argument, clarifying that it is only supported for task_type='causal_lm'. This is a helpful addition for users. To improve robustness, I've suggested adding a runtime check to enforce this constraint, which will prevent potential errors from misconfiguration. On a minor note, the pull request title [WIP] refactor template doesn't seem to accurately reflect the changes, which are focused on documentation. Consider updating it to something more descriptive like docs: Add limitation for use_liger_kernel.

[gemini-code-assist]

This documentation update is helpful. To make the implementation more robust and prevent misuse, consider adding a check in the argument parsing logic to enforce this constraint. For example, in swift/llm/argument/train_args.py, within the TrainArguments.__post_init__ method, you could add:

if getattr(self, 'use_liger_kernel', False) and self.task_type != 'causal_lm':
    raise ValueError("`use_liger_kernel` only supports `task_type='causal_lm'`.")

This would provide immediate feedback to users who try to use liger_kernel with an unsupported task type.

[gemini-code-assist]

This documentation update is helpful. To make the implementation more robust and prevent misuse, consider adding a check in the argument parsing logic to enforce this constraint. For example, in swift/llm/argument/train_args.py, within the TrainArguments.__post_init__ method, you could add:

if getattr(self, 'use_liger_kernel', False) and self.task_type != 'causal_lm':
    raise ValueError("`use_liger_kernel` only supports `task_type='causal_lm'`.")

This would provide immediate feedback to users who try to use liger_kernel with an unsupported task type.