Resolve output characters garbled

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hello ， Because I want my model to have Chinese language ability, but the language and training resources required for full parameter training of Chinese language are huge, I used the Chinese llama model trained by other open-source projects. However, I think the litgpt project is very convenient, so I converted the models from other open-source projects to a lit model. The output of the lit model has Chinese language ability, but there is character garbled phenomenon in the output text. How can I solve the character garbled phenomenon? I look forward to your reply. Thank you
(Appendix: Chinese Open Source Model GitHub Address: https://github.com/LlamaFamily/Llama-Chinese?tab=readme-ov-file
Chinese Open Source Model File Hugging Face Address: https://huggingface.co/FlagAlpha/Llama3-Chinese-8B-Instruct/tree/main

Start by reproducing the garbled output from the converted lit model and compare it with the referenced Llama-Chinese model and Hugging Face files. Done means identifying the conversion or model-resource mismatch responsible and documenting a reliable way to produce readable Chinese output.

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