FMEval
FMEval is a comprehensive evaluation suite developed by Amazon SageMaker Clarify, designed to assess the quality and responsibility of large language models (LLMs) in generative AI applications. It provides standardized implementations of metrics to evaluate question-answering assistants on an enterprise scale. The suite is particularly useful for generating ground truth data, which is essential for evaluating the performance of AI models in providing accurate and reliable answers to user queries. FMEval's approach to evaluation is rooted in best practices that ensure the models are not only effective but also responsible in their outputs. This involves assessing the models' ability to handle diverse and complex queries while maintaining a high standard of accuracy and ethical considerations. The suite is part of Amazon's broader efforts to enhance the capabilities of AI models by providing tools that facilitate rigorous testing and validation processes. By leveraging FMEval, organizations can ensure that their AI-driven solutions meet the necessary standards for deployment in real-world scenarios, thereby enhancing user trust and satisfaction.
Algorithms Used
Not specified
Model Architecture
Not specified
Datasets Used
Not specified
Performance Metrics
Quality, responsibility
Deployment Options
Not specified
Cloud Based
Yes
On Premises
No
Features
Comprehensive evaluation suite, standardized metrics, ground truth generation
Enterprise
Yes
Hardware Requirements
Not specified
Supported Platforms
Amazon SageMaker
Interoperability
Not specified
Security Features
Not specified
Compliance Standards
Not specified
Certifications
Not specified
Open Source
No
Source Code URL
Documentation URL
Community Support
Not specified
Contributors
Amazon
Training Data Size
Not specified
Inference Latency
Not specified
Energy Efficiency
Not specified
Explainability Features
Not specified
Ethical Considerations
Ensures quality and responsibility in AI outputs
Known Limitations
Not specified
Industry Verticals
Enterprise, technology
Use Cases
Evaluating question-answering assistants
Customer Base
Enterprises using Amazon SageMaker
Integration Options
Not specified
Scalability
Not specified
Support Options
Not specified
SLA
Not specified
User Interface
Not specified
Multi-Language Support
No
Localization
Not specified
Pricing Model
Not specified
Trial Availability
No
Partner Ecosystem
Amazon
Patent Information
Not specified
Regulatory Compliance
Not specified
Version
Not specified
Website URL
Service Type
Not specified
Has API
No
API Details
Not applicable
Business Model
Not specified
Price
0.00
Currency
Not specified
License Type
Not specified
Release Date
01/01/1970
Last Update Date
01/01/1970
Contact Email
Contact Phone
Not specified
Social Media Links
Other Features
Not specified
Published
Yes