[docs] update docs & update dataset 'loss'

[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 addresses a type inconsistency bug in the encode method within swift/template/base.py, ensuring that the length attribute is always returned as a list, regardless of whether it contains a single element or multiple. Additionally, it updates the documentation for supported models and datasets in both Chinese and English, adding a warning to guide users to the correct version-specific documentation.

Highlights

• Type Consistency Fix: Corrected an issue in swift/template/base.py where the length field in the encoded dictionary could be either an integer or a list of integers, ensuring it is now consistently a list.
• Documentation Update: Added a warning to both Chinese and English versions of the "Supported Models and Datasets" documentation, clarifying that the document is for swift 4.0.0 and providing a link to the v3.12 documentation for older versions.

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[gemini-code-assist]

Code Review

This pull request aims to fix an issue where the length field for reranker tasks could be either an integer or a list, causing inconsistencies. While the change in swift/template/base.py correctly addresses this for reranker tasks, it introduces a critical bug for other tasks like causal_lm when Megatron is used, as it would cause a TypeError. I have provided a more targeted fix for this issue. Additionally, I've pointed out a minor typo and a formatting issue in the documentation files.

[Jintao-Huang]

/gemini review

[gemini-code-assist]

Code Review

This PR updates the documentation for Swift 4.0.0 and refactors the loss scale calculation logic. The documentation changes are clear and helpful. The code change in swift/loss_scale/base.py simplifies how the loss value from datasets is handled. However, the conditional logic is a bit complex, and its readability could be improved. I have one suggestion to enhance readability.