Trelis/Llama-2-7b-hf-function-calling
The Trelis/Llama-2-7b-hf-function-calling model is a 7 billion parameter Llama 2-based language model developed by Trelis, specifically fine-tuned to extend the Llama 2 architecture with function calling capabilities. This model responds with structured JSON arguments for function names and parameters, making it optimized for tool use and integration with external systems. It supports a 4096 token context length and is designed for applications requiring programmatic interaction with functions.
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Overview
Trelis/Llama-2-7b-hf-function-calling is a 7 billion parameter model built upon the Llama 2 architecture, developed by Trelis. Its core differentiator is the integration of function calling capabilities, allowing it to respond with structured JSON objects that specify function names and their arguments. This enables seamless interaction with external tools and APIs, making it highly suitable for agentic workflows.
Key Capabilities
- Function Calling: Generates structured JSON responses for function invocation, including function name and arguments.
- Llama 2 Foundation: Benefits from the robust base capabilities of the Llama 2 7B model, including a 4096 token context length.
- Optimized for Tool Use: Specifically trained to understand and execute function calls based on user prompts and provided function metadata.
- Multiple Quantization Formats: Available in various formats, including bitsandbytes NF4, GPTQ, and GGML, catering to different deployment needs from cloud GPUs to local machines (e.g., Mac).
Good For
- Building AI Agents: Ideal for creating agents that need to interact with external systems, databases, or APIs by calling specific functions.
- Automated Workflows: Automating tasks that require structured outputs to trigger subsequent actions.
- Developers Integrating LLMs with Tools: Simplifies the process of connecting language models to custom or third-party tools and services.
- Resource-Efficient Function Calling: Provides function calling capabilities on a 7B parameter model, offering a balance between performance and computational cost.