Display model benchmark results
Export Hugging Face models to ONNX
Calculate survival probability based on passenger details
Track, rank and evaluate open LLMs and chatbots
Download a TriplaneGaussian model checkpoint
Optimize and train foundation models using IBM's FMS
Convert PaddleOCR models to ONNX format
Benchmark models using PyTorch and OpenVINO
Measure over-refusal in LLMs using OR-Bench
GIFT-Eval: A Benchmark for General Time Series Forecasting
Browse and filter ML model leaderboard data
Measure BERT model performance using WASM and WebGPU
Evaluate adversarial robustness using generative models
The Redteaming Resistance Leaderboard is a tool designed for model benchmarking, specifically to evaluate and compare the performance of AI models in resisting adversarial attacks. It provides a comprehensive platform to display and analyze benchmark results, helping researchers and developers identify robust models capable of withstanding various adversarial scenarios.
• Leaderboard Display: Presents model benchmark results in a clear and structured format.
• Filtering Options: Allows users to narrow down results based on specific criteria.
• Detailed Metrics: Offers in-depth insights into model performance across different attack vectors.
• Visualization Tools: Includes charts and graphs to help users better understand the data.
• Export Data: Provides functionality to download results for further analysis.
What is the purpose of the Redteaming Resistance Leaderboard?
The leaderboard is designed to benchmark AI models based on their resistance to adversarial attacks, providing a clear comparison of their robustness and performance.
How often are the results updated?
Results are updated regularly as new models and datasets are added to the benchmarking platform.
Can I use the leaderboard for commercial purposes?
Yes, the leaderboard is available for public use, including commercial applications, provided proper attribution is made.