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How to achieve capability migration for Qwen3 fine-tuning models in cross-language scenarios?

2025-08-28 272
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Cross-Language Migration Implementation Program

To realize the extension of the model's multilingual capabilities, it can be advanced in three phases:

  • Data preparation::
    • Constructing a parallel corpus (combinations of Chinese/English/Chinese/Japanese etc. are recommended)
    • existdata/Catalog New Creationmultilingual.jsonThe field containslanguage_tag
  • blended training::
    • Keep the original model word list and add it with SFT scripts--lang_loss_weight 0.3parameters
    • Recommended mixed multilingual samples within batch (supported by project dataloader)
  • capability testing::
    • Specify during interaction testing--language enParameters such as switching language
    • Quantitative assessment using indicators such as BLEU

Note: Smaller size models (1.7B) are recommended to focus on single language pairs, while models above 4B can try joint multi-language training.

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