XLAM

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xLAM is an AI Agents & Automation tool that provides a family of Large Action Models to empower AI agent systems. It offers models for general tasks and function calling, with open-source components for research and development.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Yes

Skill level

Technical

About

What is xLAM?

xLAM is a comprehensive platform offering a family of Large Action Models (LAMs) designed to enhance AI agent systems. It aggregates agent trajectories from diverse environments, standardizing them into a consistent format for optimized agent training. The platform includes various models, such as Llama-xLAM-2-70b-fc-r and xLAM-2-1b-fc-r, which are fine-tuned for broad agentic capabilities and specialized function calling tasks. xLAM also provides ActionStudio, a lightweight framework for agentic data and training, and APIGen-MT for multi-turn data generation. The models are compatible with VLLM, FastChat, and Transformers-based inference frameworks, making them suitable for researchers and developers looking to deploy and interact with advanced AI agents.

Best used for

Ideal for researchers and developers who need to build and train advanced AI agent systems, fine-tune models for specific function-calling tasks, and generate multi-turn agentic data. Especially valuable for those working on autonomous agents and requiring robust, open-source large action models.

Common actions

develop AI agents

train large action models

deploy function-calling models

generate agentic data

github copilotface swapping"AI Agents"automated workflowcollaborationopen-sourcelow-code/no-codedeepfakeworkflows

Capabilities

Key features

Large Action Models
Function calling
Agent trajectory aggregation
ActionStudio framework
APIGen-MT data generation
VLLM/Transformers compatibility

Target Audience

professordeveloperresearcher

Integrations

hugging-facevllmfastchattransformers

Pricing & Plans

Open Source

Free

FAQs

What are the primary applications of xLAM models?

xLAM models are primarily used for empowering AI agent systems, supporting both general tasks and specialized function calling. They are designed to handle multi-turn conversations and complex agent trajectories, making them suitable for developing sophisticated autonomous agents.

How can I deploy xLAM models for inference?

xLAM models can be efficiently deployed using various inference frameworks, including Transformers and vLLM. The repository provides examples for both, with vLLM offering high-throughput inference capabilities, especially for larger models. A tool parser plugin is available for vLLM deployment.

Is xLAM suitable for research purposes only?

Yes, the xLAM repository and its associated data are provided for research purposes only. While the models offer impressive capabilities, their release is partially regulated due to internal policies, focusing on advancing the agent research community.

What is ActionStudio and how does it relate to xLAM?

ActionStudio is a lightweight framework included within the xLAM ecosystem. It is designed for agentic data and training of Large Action Models. It helps in managing training configurations and enhancing the overall development process for AI agents.

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Research & Education › Academic Research Coding & Development › Open Source & Models

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