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Mistral 7B: Engineering Extreme Efficiency in LLMs

https://flashpapers.ai/p/b53kqz9ne7
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Albert Q. Jiang, Alexandre Sablayrolles +16 more
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MMLU:60.1%· MMLUHumanEval:30.5%· HumanEvalGSM8K:52.2%· GSM8KHellaSwag:81.3%· HellaSwag
Abstract

We introduce Mistral 7B v0.1, a 7-billion-parameter language model engineered for superior performance and efficiency. Mistral 7B outperforms Llama 2 13B across all evaluated benchmarks, and Llama 1 34B in reasoning, mathematics, and code generation. Our model leverages grouped-query attention (GQA) for faster inference, coupled with sliding window attention (SWA) to effectively handle sequences of arbitrary length with a reduced inference cost. We also provide a model fine-tuned to follow instructions, Mistral 7B -- Instruct, that surpasses the Llama 2 13B -- Chat model both on human and automated benchmarks. Our models are released under the Apache 2.0 license.