This work introduces Gemma, a family of lightweight, state-of-the art open
models built from the research and technology used to create Gemini models.
Gemma models demonstrate strong performance across academic benchmarks for
language understanding, reasoning, and safety. We release two sizes of models
(2 billion and 7 billion parameters), and provide both pretrained and
fine-tuned checkpoints. Gemma outperforms similarly sized open models on 11 out
of 18 text-based tasks, and we present comprehensive evaluations of safety and
responsibility aspects of the models, alongside a detailed description of model
development. We believe the responsible release of LLMs is critical for
improving the safety of frontier models, and for enabling the next wave of LLM
innovations.

Gemma 是一种轻量级的、最先进的开放模型系列，从用于创建 Gemini 模型的研究和技术中构建而来。Gemma 模型在语言理解、推理和安全性等学术基准测试中表现出强大的性能。我们发布了两个规模的模型（20 亿和 70 亿参数），并提供预训练和微调的检查点。Gemma 在 18 个基于文本的任务中，有 11 个任务优于类似规模的开放模型。我们全面评估了模型的安全性和责任方面，同时详细描述了模型的开发过程。我们认为，负责任地发布 LLM 对于提高前沿模型的安全性，并推动 LLM 的下一波创新至关重要。