Launch web-based model application
Explain GPU usage for model training
Calculate memory usage for LLM models
Submit models for evaluation and view leaderboard
Export Hugging Face models to ONNX
Merge machine learning models using a YAML configuration file
Merge Lora adapters with a base model
Rank machines based on LLaMA 7B v2 benchmark results
Evaluate model predictions with TruLens
Run benchmarks on prediction models
Analyze model errors with interactive pages
Text-To-Speech (TTS) Evaluation using objective metrics.
Determine GPU requirements for large language models
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.