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Explore the development of intelligent agents using gemma models, with core components that facilitate agent creation, including capabilities for function calling, planning, and reasoning The gemma 3 models are multimodal—processing text and images—and feature a 128k context window with support for over 140 languages. 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 3 is designed to work seamlessly with popular ml frameworks including pytorch, tensorflow, and jax Gemma is a lightweight, family of models from google built on gemini technology We provide optimized implementations and integration guides for each framework.
This repository contains the implementation of the gemma pypi package.
Eam, google deepmind1 we introduce gemma 3, a multimodal addition to the gemma family of lightweight open models, ranging in scale from 1 to 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. 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.
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Summary description and brief definition of inputs and outputs
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