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  We achieve the following MT-Bench scores across 6 languages:
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  # Training data
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  We achieve the following MT-Bench scores across 6 languages:
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+ | | **meta-llama/Meta-Llama-3-8B-Instruct** | **lightblue/suzume-llama-3-8B-multilingual** | **Nexusflow/Starling-LM-7B-beta** | **gpt-3.5-turbo** |
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+ |-----------------|-----------------------------------------|----------------------------------------------|-----------------------------------|-------------------|
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+ | **German** πŸ‡©πŸ‡ͺ | NaN | 7.26 | 6.99 | 7.68 |
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+ | **French** πŸ‡«πŸ‡· | NaN | 7.66 | 7.29 | 7.74 |
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+ | **Japanese** πŸ‡―πŸ‡΅ | NaN | 6.56 | 6.22 | 7.84 |
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+ | **Russian** πŸ‡·πŸ‡Ί | NaN | 8.19 | 8.28 | 7.94 |
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+ | **Chinese** πŸ‡¨πŸ‡³ | NaN | 7.11 | 6.97 | 7.55 |
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+ | **English** πŸ‡ΊπŸ‡Έ | 7.98 | 7.73 | 7.92 | 8.26 |
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+ We observe minimal degredation of Llama 3's English ability while achieving best-in-class multilingual abilities compared to the top rated 7B model on the [Chatbot Arena Leaderboard](https://chat.lmsys.org/?leaderboard).
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  # Training data
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