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## Evaluation
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This model was evaluated on the well-known Arena-Hard, OpenLLM v1, OpenLLM v2, and HumanEval benchmarks.
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This version of the lm-evaluation-harness includes versions of MMLU, ARC-Challenge and GSM-8K that match the prompting style of [Meta-Llama-3.1-Instruct-evals](https://huggingface.co/datasets/meta-llama/Meta-Llama-3.1-70B-Instruct-evals) and a few fixes to OpenLLM v2 tasks.
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**Note:** Results have been updated after Meta modified the chat template.
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## Evaluation
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This model was evaluated on the well-known Arena-Hard, OpenLLM v1, OpenLLM v2, and HumanEval benchmarks.
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In all cases, model outputs were generated with the [vLLM](https://docs.vllm.ai/en/stable/) engine.
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Arena-Hard evaluations were conducted using the [Arena-Hard-Auto](https://github.com/lmarena/arena-hard-auto) repository.
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OpenLLM v1 and v2 evaluations were conducted using Neural Magic's fork of [lm-evaluation-harness](https://github.com/neuralmagic/lm-evaluation-harness/tree/llama_3.1_instruct) (branch llama_3.1_instruct).
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This version of the lm-evaluation-harness includes versions of MMLU, ARC-Challenge and GSM-8K that match the prompting style of [Meta-Llama-3.1-Instruct-evals](https://huggingface.co/datasets/meta-llama/Meta-Llama-3.1-70B-Instruct-evals) and a few fixes to OpenLLM v2 tasks.
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HumanEval and HumanEval+ evaluations were conducted using Neural Magic's fork of the [EvalPlus](https://github.com/neuralmagic/evalplus) repository.
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**Note:** Results have been updated after Meta modified the chat template.
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