katanemo/Arch-Agent-7B
katanemo/Arch-Agent-7B is a 7.6 billion parameter large language model from katanemo, specifically designed for advanced function calling and agent-based applications. It excels at multi-turn and multi-step function calling, enabling sophisticated workflows that require intelligent tool selection and adaptive planning. This model is optimized for complex agentic tasks, providing reliable and precise performance across extended function call sequences.
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Arch-Agent-7B: Advanced Function Calling for Agentic Workflows
Arch-Agent-7B is a 7.6 billion parameter model developed by katanemo, part of the Arch-Agent series, specifically engineered for robust function calling and agent-based applications. It is designed to manage complex, multi-step tasks by intelligently selecting tools, planning adaptively, and integrating seamlessly with external APIs.
Key Capabilities
- Multi-Turn Function Calling: Maintains context across dialogues for natural, evolving tool use.
- Multi-Step Function Calling: Plans and executes sequences of function calls, dynamically adapting to intermediate results and decomposing goals.
- Agentic Capabilities: Provides advanced decision-making and workflow management for complex tasks, including tool coordination and error recovery.
Performance
Arch-Agent-7B demonstrates leading performance on the Berkeley Function-Calling Leaderboard (BFCL), showcasing its proficiency in complex function-calling scenarios. The model is evaluated with a context length of 64K, utilizing YaRN scaling for multi-turn evaluations.
Good For
- Developers building sophisticated AI agents requiring reliable function calling.
- Applications needing to manage multi-step and multi-turn interactions with external tools.
- Scenarios demanding precise and adaptive planning for complex tasks.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.