Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Launch top-notch LLM applications swiftly while maintaining rigorous testing standards. You should never feel constrained by the intricate and often subjective aspects of LLM interactions. Generative AI often yields subjective outcomes, and determining the quality of generated content frequently necessitates the expertise of a subject matter professional. If you're developing an LLM application, you're likely aware of the myriad constraints and edge cases that must be managed before a successful release. Issues such as hallucinations, inaccurate responses, biases, policy deviations, and potentially harmful content must all be identified, investigated, and addressed both prior to and following the launch of your application. Deepchecks offers a solution that automates the assessment process, allowing you to obtain "estimated annotations" that only require your intervention when absolutely necessary. With over 1000 companies utilizing our platform and integration into more than 300 open-source projects, our core LLM product is both extensively validated and reliable. You can efficiently validate machine learning models and datasets with minimal effort during both research and production stages, streamlining your workflow and improving overall efficiency. This ensures that you can focus on innovation without sacrificing quality or safety.
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.
API Access
Has API
No
API Access
Has API
Yes
Integrations
Amazon SageMaker
Yes
Llama
No
Nebius Token Factory
No
OpenAI
No
Python
Yes
ZenML
Yes
Integrations
Amazon SageMaker
No
Llama
Yes
Nebius Token Factory
Yes
OpenAI
Yes
Python
No
ZenML
No
Pricing Details
$1,000 per month
Free Trial
Yes
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
No
In Person
Yes
Vendor Details
Company Name
Deepchecks
Founded
2019
Country
United States
Website
deepchecks.com
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/