Gemma is a family of generative artificial intelligence (ai) models and you can use them in a wide variety of generation tasks, including question answering, summarization, and reasoning. Gemma is a lightweight, family of models from google built on gemini technology The gemma 3 models are multimodal—processing text and images—and feature a 128k context window with support for over 140 languages. Gemma 3 is designed to work seamlessly with popular ml frameworks including pytorch, tensorflow, and jax We provide optimized implementations and integration guides for each framework. Gemma is a family of lightweight, generative artificial intelligence (ai) open models, built from the same research and technology used to create the gemini models.
Explore google's gemma ai models — from lightweight 2b llms to multimodal 27b powerhouses Learn about gemma's architecture, use cases, performance, and how to run inference using vllm. In this section, we focus on some key diferences from pr 5:1 interleaving of local/global layers Google sees the new gemma being used for tasks like text classification and data analysis, which it can accomplish quickly and without heavy computing requirements. Developed by google deepmind and other teams across google, gemma is named after the latin gemma, meaning precious stone The gemma model weights are supported by developer tools that promote innovation, collaboration, and the responsible use of artificial intelligence (ai).
