Trelis/Llama-2-7b-chat-hf-function-calling-v2

Trelis Llama-2-7b-chat-hf-function-calling-v2 Overview

This model is a 7 billion parameter Llama 2 chat model, developed by Trelis, specifically fine-tuned for function calling. It extends the base Llama 2 architecture to enable structured JSON responses, facilitating integration with external tools and APIs. This version (v2) introduces significant improvements over its predecessor, including a simplified syntax where only function descriptions are needed for inference, and function descriptions are moved outside the system prompt to prevent influence from system prompt training.

Key Capabilities

• Function Calling: Generates structured JSON outputs containing function names and arguments, enabling seamless interaction with external tools.
• Simplified Syntax: Requires only function descriptions for inference, streamlining the development process.
• Robust Prompting: Function descriptions are isolated from the system prompt, ensuring consistent function calling behavior.
• Llama 2 Base: Benefits from the strong conversational capabilities of the underlying Llama 2 7B chat model.
• Flexible Argument Handling: Fine-tuned on argument types including strings, numbers, and arrays, supporting functions with 0, 1, 2, or 3 arguments.

Good For

• Tool-use and Agent Development: Ideal for building AI agents that need to interact with external systems or databases.
• Structured Output Generation: Use cases requiring precise, machine-readable outputs for automation or integration.
• Conversational AI with External Actions: Enhancing chatbots or virtual assistants with the ability to perform actions like searching the web, booking appointments, or retrieving specific data.
• Developers seeking a free function-calling model: This specific 7B Llama 2 variant is offered for free, unlike many other Trelis function-calling models.