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Description
Llama Guard is a collaborative open-source safety model created by Meta AI aimed at improving the security of large language models during interactions with humans. It operates as a filtering mechanism for inputs and outputs, categorizing both prompts and replies based on potential safety risks such as toxicity, hate speech, and false information. With training on a meticulously selected dataset, Llama Guard's performance rivals or surpasses that of existing moderation frameworks, including OpenAI's Moderation API and ToxicChat. This model features an instruction-tuned framework that permits developers to tailor its classification system and output styles to cater to specific applications. As a component of Meta's extensive "Purple Llama" project, it integrates both proactive and reactive security measures to ensure the responsible use of generative AI technologies. The availability of the model weights in the public domain invites additional exploration and modifications to address the continually changing landscape of AI safety concerns, fostering innovation and collaboration in the field. This open-access approach not only enhances the community's ability to experiment but also promotes a shared commitment to ethical AI development.
Description
Current models are costly to train, complicated to implement, challenging to validate, and notoriously susceptible to generating misleading information. At Symbolica, we are reimagining the process of machine learning from its foundation. By leveraging the highly expressive framework of category theory, we create models that can learn and understand algebraic structures. This approach equips our models with a comprehensive and systematic representation of the world that is both explainable and verifiable. Our goal is to empower developers and end users to grasp and articulate the reasons behind model outputs. This level of interpretability and control over the outputs—such as the ability to remove proprietary data from the training set—is essential for applications that are critical to mission success. Additionally, we believe that enhancing transparency in how models derive their conclusions will foster greater trust and collaboration between humans and machines.
API Access
Has API
API Access
Has API
Integrations
Llama
OpenAI
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Meta
Founded
2004
Country
United States
Website
ai.meta.com/research/publications/llama-guard-llm-based-input-output-safeguard-for-human-ai-conversations/
Vendor Details
Company Name
Symbolica
Website
www.symbolica.ai
Product Features
Product Features
Artificial Intelligence
Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)