March 14, 2024, 4:48 a.m. | Gemma Team, Thomas Mesnard, Cassidy Hardin, Robert Dadashi, Surya Bhupatiraju, Shreya Pathak, Laurent Sifre, Morgane Rivi\`ere, Mihir Sanjay Kale, Jul

cs.CL updates on arXiv.org arxiv.org

arXiv:2403.08295v1 Announce Type: new
Abstract: 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 …

abstract academic art arxiv benchmarks billion cs.ai cs.cl family gemini gemma language language understanding open models performance reasoning release research safety state technology type understanding work

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