Explore and filter model evaluation results
Calculate VRAM requirements for running large language models
Display server status information
Migrate datasets from GitHub or Kaggle to Hugging Face Hub
Finance chatbot using vectara-agentic
Filter and view AI model leaderboard data
Gather data from websites
Generate detailed data reports
This project is a GUI for the gpustack/gguf-parser-go
Monitor application health
Life System and Habit Tracker
Compare classifier performance on datasets
Analyze and visualize your dataset using AI
GTBench is a data visualization tool designed to help users explore and filter model evaluation results. It provides an interactive interface to analyze and compare performance metrics of different models, enabling deeper insights into their effectiveness.
• Interactive Visualization: Explore model performance through dynamic and customizable visualizations. • Advanced Filtering: Apply filters to narrow down results based on specific criteria such as model type, dataset, or performance metrics. • Real-Time Updates: Get instant feedback as you adjust filters or visualization settings. • Multi-Model Support: Compare results from multiple models in a single interface. • Customizable Dashboards: Tailor the layout to focus on the metrics that matter most. • Export Capabilities: Save and share visualizations or raw data for further analysis.
What does GTBench stand for?
GTBench stands for Graph Tool Benchmark, a utility for analyzing and visualizing model evaluation data.
Can I use GTBench for models other than graphs?
Yes, GTBench supports a variety of model types, including but not limited to graph-based models.
How do I export visualization results from GTBench?
To export results, use the "Export" button in the toolbar, which allows you to save visualizations as images or raw data as CSV files.