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  # Updates
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- - πŸš€πŸš€πŸš€ [July 24, 2024] We now introduce [shenzhi-wang/Llama3.1-8B-Chinese-Chat](https://huggingface.co/shenzhi-wang/Llama3.1-8B-Chinese-Chat)! Compared to the original [Meta-Llama-3.1-8B-Instruct model](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct), our llama3.1-8B-Chinese-Chat model significantly reduces the issues of "Chinese questions with English answers" and the mixing of Chinese and English in responses. The training dataset contains >100K preference pairs, and it exhibits significant enhancements, especially in **roleplay**, **function calling**, and **math** capabilities!
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  - πŸ”₯ We provide the official **q4_k_m, q8_0, and f16 GGUF** versions of Llama3.1-8B-Chinese-Chat-**v2.1** at https://huggingface.co/shenzhi-wang/Llama3.1-8B-Chinese-Chat/tree/main/gguf!
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  This is the first model specifically fine-tuned for Chinese & English users based on the [Meta-Llama-3.1-8B-Instruct model](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct). The fine-tuning algorithm used is ORPO [1].
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- **Compared to the original [Meta-Llama-3.1-8B-Instruct model](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct), our llama3.1-8B-Chinese-Chat model significantly reduces the issues of "Chinese questions with English answers" and the mixing of Chinese and English in responses.**
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  [1] Hong, Jiwoo, Noah Lee, and James Thorne. "Reference-free Monolithic Preference Optimization with Odds Ratio." arXiv preprint arXiv:2403.07691 (2024).
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  # Updates
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+ - πŸš€πŸš€πŸš€ [July 24, 2024] We now introduce [shenzhi-wang/Llama3.1-8B-Chinese-Chat](https://huggingface.co/shenzhi-wang/Llama3.1-8B-Chinese-Chat)! The training dataset contains >100K preference pairs, and it exhibits significant enhancements, especially in **roleplay**, **function calling**, and **math** capabilities!
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  - πŸ”₯ We provide the official **q4_k_m, q8_0, and f16 GGUF** versions of Llama3.1-8B-Chinese-Chat-**v2.1** at https://huggingface.co/shenzhi-wang/Llama3.1-8B-Chinese-Chat/tree/main/gguf!
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  This is the first model specifically fine-tuned for Chinese & English users based on the [Meta-Llama-3.1-8B-Instruct model](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct). The fine-tuning algorithm used is ORPO [1].
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  [1] Hong, Jiwoo, Noah Lee, and James Thorne. "Reference-free Monolithic Preference Optimization with Odds Ratio." arXiv preprint arXiv:2403.07691 (2024).
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