Launch web-based model application
Submit deepfake detection models for evaluation
Download a TriplaneGaussian model checkpoint
Request model evaluation on COCO val 2017 dataset
Text-To-Speech (TTS) Evaluation using objective metrics.
Explore and benchmark visual document retrieval models
Convert PaddleOCR models to ONNX format
Evaluate LLM over-refusal rates with OR-Bench
Merge machine learning models using a YAML configuration file
Measure over-refusal in LLMs using OR-Bench
View LLM Performance Leaderboard
Optimize and train foundation models using IBM's FMS
Display genomic embedding leaderboard
AICoverGen is a web-based application designed for model benchmarking, enabling users to evaluate AI models efficiently. It provides a user-friendly interface to launch and manage model benchmarking tasks, catering to both experts and non-experts. The tool simplifies the process of comparing and analyzing AI models, making it accessible for a broad range of users.
• Automated Benchmarking: AICoverGen streamlines the benchmarking process with minimal manual intervention. • Customizable Benchmarks: Users can define specific criteria and metrics for evaluation. • Real-Time Results: Generates performance metrics and insights in real-time for quick decision-making. • Cross-Model Compatibility: Supports benchmarking across multiple AI models and frameworks. • Data Visualization: Provides detailed charts and graphs to compare model performance effectively. • Flexible Deployment: Compatible with both cloud-based and on-premises environments.
What models does AICoverGen support?
AICoverGen supports a wide range of AI models, including popular frameworks like TensorFlow, PyTorch, and more.
Do I need advanced technical skills to use AICoverGen?
No, AICoverGen is designed to be user-friendly, allowing even non-experts to benchmark models effectively.
How long does the benchmarking process take?
The duration depends on the model size and selected benchmarking parameters. AICoverGen optimizes the process for faster results.