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As with any large language model, users should be aware of potential biases and limitations. We recommend implementing appropriate safeguards and human oversight when deploying this model in production environments.
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_MaziyarPanahi__calme-2.1-qwen2-72b)
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| Metric |Value|
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|Avg. |43.61|
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|IFEval (0-Shot) |81.63|
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|BBH (3-Shot) |57.33|
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|MATH Lvl 5 (4-Shot)|36.03|
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|GPQA (0-shot) |17.45|
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|MuSR (0-shot) |20.15|
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|MMLU-PRO (5-shot) |49.05|
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As with any large language model, users should be aware of potential biases and limitations. We recommend implementing appropriate safeguards and human oversight when deploying this model in production environments.
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