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What is Llama Guard?

Llama Guard is an innovative open-source safety model developed by Meta AI that seeks to enhance the security of large language models during their interactions with users. It functions as a filtering system for both inputs and outputs, assessing prompts and responses for potential safety hazards, including toxicity, hate speech, and misinformation. Trained on a carefully curated dataset, Llama Guard competes with or even exceeds the effectiveness of current moderation tools like OpenAI's Moderation API and ToxicChat. This model incorporates an instruction-tuned framework, allowing developers to customize its classification capabilities and output formats to meet specific needs. Part of Meta's broader "Purple Llama" initiative, it combines both proactive and reactive security strategies to promote the responsible deployment of generative AI technologies. The public release of the model weights encourages further investigation and adaptations to keep pace with the evolving challenges in AI safety, thereby stimulating collaboration and innovation in the domain. Such an open-access framework not only empowers the community to test and refine the model but also underscores a collective responsibility towards ethical AI practices. As a result, Llama Guard stands as a significant contribution to the ongoing discourse on AI safety and responsible development.

What is LLM Guard?

LLM Guard provides a comprehensive array of safety measures, such as sanitization, detection of harmful language, prevention of data leaks, and protection against prompt injection attacks, to guarantee that your interactions with large language models remain secure and protected. Designed for easy integration and deployment in practical settings, it operates effectively from the outset. While it is immediately operational, it's worth noting that our team is committed to ongoing improvements and updates to the repository. The core functionalities depend on only a few essential libraries, and as you explore more advanced features, any additional libraries required will be installed automatically without hassle. We prioritize a transparent development process and warmly invite contributions to our project. Whether you're interested in fixing bugs, proposing new features, enhancing documentation, or supporting our cause, we encourage you to join our dynamic community and contribute to our growth. By participating, you can play a crucial role in influencing the future trajectory of LLM Guard, making it even more robust and user-friendly. Your engagement not only benefits the project but also enriches the overall experience for all users involved.

Media

Media

Integrations Supported

Llama
Nebius Token Factory
OpenAI

Integrations Supported

Python

API Availability

Has API

API Availability

Pricing Information

Pricing not provided

Pricing Information

Free
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

Meta

Date Founded

2004

Company Location

United States

Company Website

ai.meta.com/research/publications/llama-guard-llm-based-input-output-safeguard-for-human-ai-conversations/

Company Facts

Organization Name

LLM Guard

Company Website

llm-guard.com

Categories and Features

AI Development

Not specified

AI Guardrails

Not specified

Categories and Features

AI Guardrails

Not specified

AI Security

Not specified

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