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Introducing Arcee Agent: A Specialized 7B Language Model for Function Calling and Tool Use

Arcee Agent is yet another Arcee model punching above its weight: it's just 7B (initialized from Qwen2-7B) and outranks much larger models. Try it out for function calling and tool use!

Introducing Arcee Agent: A Specialized 7B Language Model for Function Calling and Tool Use

We are excited to announce the release of Arcee Agent, a cutting-edge 7B parameter language model designed specifically for function calling and tool use. Initialized from Qwen2-7B, Arcee Agent offers performance comparable to much larger models while maintaining efficiency and speed.

Key Features

  1. Advanced Function Calling: Excels at interpreting, executing, and chaining function calls.
  2. Multiple Format Support: Compatible with various tool use formats, including Glaive FC v2, Salesforce, and Agent-FLAN.
  3. Dual-Mode Functionality:
    • Tool Router: Can serve as intelligent middleware for request analysis and routing.
    • Standalone Chat Agent: Capable of human-like conversations and independent task completion.
  4. Efficient Performance: Delivers rapid response times, suitable for real-time applications and resource-constrained environments.

Capabilities

Arcee Agent is particularly adept at:

  • API Integration
  • Database Operations
  • Code Generation and Execution
  • Multi-step Task Execution

Business Use Cases

Arcee Agent can be applied across various industries for tasks such as:

  • Customer Support Automation
  • Sales and Marketing Automation
  • Operational Efficiency Enhancement
  • Financial Services Automation
  • Healthcare Solutions
  • E-commerce Enhancements
  • Human Resources Automation
  • Legal Services Automation
  • Educational Tools
  • Manufacturing and Supply Chain Automation

Availability and Training

Arcee Agent was trained using Spectrum, with compute provided by CrusoeAI.

Limitations

Users should be aware that:

  • The model's capabilities outside function calling and tool use may be more limited compared to larger, general-purpose models.
  • As with all language models, outputs should be validated and used responsibly.

We invite developers, researchers, and businesses to explore Arcee Agent's capabilities for implementing sophisticated AI-driven solutions without the computational overhead of larger language models.

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For more information and access to the model:
• Arcee Agent model card on Hugging Face
Quantized Model

Benchmarking

Arcee-Agent-Evals