Models Mistralv01

Salesforce/xLAM-7b-r

Warm
Public
7B
FP8
4096
Aug 28, 2024
License: cc-by-nc-4.0
Hugging Face
Overview

Overview

Salesforce/xLAM-7b-r is part of the xLAM (Large Action Models) family developed by Salesforce AI Research. These models are specifically engineered to empower AI agents by enhancing decision-making and translating user intentions into executable actions. xLAMs autonomously plan and execute tasks, serving as the "brains" for AI agents to automate workflow processes across various domains.

Key Capabilities

  • Action-Oriented AI: Designed to convert user intentions into concrete, executable actions, making it ideal for agentic applications.
  • Function-Calling Optimization: This 7.24 billion parameter model is optimized for both general agent applications and function-calling, enabling it to interact with external tools and APIs.
  • Multi-Turn Interaction Support: The model supports complex multi-turn conversations, allowing for dynamic and adaptive task execution based on ongoing user input and environmental responses.
  • JSON Output for Tool Calls: It generates API requests in a structured JSON format, similar to OpenAI's function-calling mode, facilitating seamless integration with external systems.
  • Extended Context Length: Features a 32k context length, allowing it to process and maintain longer interaction histories and complex task descriptions.

Benchmarks & Performance

xLAM-7b-r demonstrates strong performance across several action-oriented benchmarks:

  • Berkeley Function-Calling Leaderboard (BFCL): Achieves competitive results in overall accuracy, indicating robust function-calling capabilities.
  • Webshop and ToolQuery: Shows solid success rates on these benchmarks, highlighting its ability to navigate and interact with web environments and query tools effectively.
  • Unified ToolQuery: Performs well on the Unified ToolQuery dataset, further validating its proficiency in tool utilization.
  • ToolBench: Exhibits good pass rates on ToolBench across various scenarios, showcasing its generalizability in complex tool-use tasks.

Usage & Integration

The model is designed for easy integration with Hugging Face's transformers library. It provides a specific prompt format and helper functions to ensure optimal performance, particularly for extracting JSON-formatted tool calls. The release is currently for research purposes, with an enhanced version planned for Salesforce customers.