Explore the development of intelligent agents using gemma models, with core components that facilitate agent creation, including capabilities for function calling, planning, and reasoning. These are the main paths you can follow when using gemma models in an application: 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.
This repository contains the implementation of the gemma pypi package. Developed by google deepmind and other teams across google, gemma is inspired by gemini, and the name reflects the latin gemma, meaning “precious stone.” It is based on similar technologies as gemini
Today google releases gemma 3, a new iteration of their gemma family of models The models range from 1b to 27b parameters, have a context window up to 128k tokens, can accept images and text, and support 140+ languages Try out gemma 3 now 👉🏻 gemma 3 space All the models are on the hub and tightly integrated with the hugging face ecosystem.
It is the best model that fits in a single consumer gpu or tpu host. 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.
