Multi-language code conversion optimization solution
Qwen3-Coder supports the conversion of 92 programming languages to each other, in order to ensure conversion accuracy should be:
- Clarification of linguistic norms: Specify the source and target language versions in the prompt, for example
"Convert this Python 3.8 code to Java 11" - provide contextual information: Preserve comments and type hints in the original code to help the model understand the programming intent
- Using Intermediate Templates: For complex conversions, let the model generate pseudo-code before converting it to the target language.
- Setting the language identifier: Use in Prompt
<|language_python|>etc. markers clarify the linguistic context - Step-by-step verification mechanism: Implemented through the Qwen Code tool
qwen > Verify the semantic equivalence between these two code snippets
For system-level code conversion, it is recommended:
1. Rapid generation of candidate scenarios using smaller models such as 7B/14B first
2. Fine optimization with the 480B large model again
3. Finally, the RAG function was used to retrieve similar conversion cases for comparison.
This answer comes from the articleQwen3-Coder: open source code generation and intelligent programming assistantThe
May not be reproduced without permission:AI productivity tools " How to improve the accuracy of Qwen3-Coder in multilingual code conversion tasks?
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