Binding functions to LLMs allows seamless generation of payloads for tool execution. Local LLMs like the fine-tuned Llama 3 model offer robust performance for tool calling.

With an open, plug-and-play architecture, MCP is the key to enabling AI agents to interact seamlessly with external tools and ...

Katanemo's new Arch-Function LLMs promise 12x faster function-calling capabilities, empowering enterprises to build ultra-fast, cost-effective agentic AI applications.

Trelis Tiny Trelis Tiny, a model with 1.3 billion parameters, stands out for its ability to perform function calling, a feature crucial for dynamic and interactive tasks.

More information: Nandan Kumar Jha et al, Entropy-Guided Attention for Private LLMs, arXiv (2025). DOI: 10.48550/arxiv.2501.03489 Provided by NYU Tandon School of Engineering ...