gemma 支持agent能力吗？是需要自己微调出来吗
gemma 支持agent能力吗？是需要自己微调出来吗
Gemma models are vital for building AI agents or can say acting as their "brain" for reasoning and planning. Gemma, as a family of lightweight, open generative AI models plays a significant role in supporting the development of AI agents by providing the core language model capabilities that enable agents to reason, plan and interact with their environment.
They enable agents to use tools(Function Calling): Modern AI agents need to interact with external tools, APIs and systems to perform tasks beyond just generating text. This is where "function calling" comes in. While earlier Gemma versions had limited built-in function calling but newer versions like Gemma 3 offer native function calling and structured outputs, allowing agents to seamlessly connect with external services.
Adapt to tasks through customization(Fine-tuning): Gemma's open-weight nature allows developers to fine-tune the models on specific datasets. This means you can train a Gemma-based agent to handle niche industry workflows, learn custom tools or specialize in particular tasks, making them highly adaptable to various agentic applications and run efficiently on local devices from laptops and desktops to mobile devices and edge devices.
Newer versions(PaliGemma, Gemma 3, Gemma 3n) also offer multimodal capabilities which can process text, images, audio and vidoe allowing agents to handle a wider range of tasks and extended context like Gemma 3 offering a 128k-token context window, agents can process and understand vast amounts of information in a single prompt, allowing for more complex analysis and longer, more coherent interactions, supported by a strong ecosystem and Tools.
Gemma is supported by popular frameworks like Hugging Face Transformers, Keras, PyTorch, and tools like Ollama and Gemma.cpp, which simplify the process of building, customizing and deploying Gemma-powered agents and provides better safety features as Google has built Gemma with comprehensive safety features, including data filtering, supervised fine-tuning and reinforcement learning with human feedback (RLHF), contributing to the development of responsible AI agents, making them ideal for developing capable AI agents.
Please have a look at this video Building intelligent agents with Gemma 3 for more details. Thank you