Display model benchmark results
Explore and submit models using the LLM Leaderboard
Rank machines based on LLaMA 7B v2 benchmark results
Evaluate AI-generated results for accuracy
Explore and benchmark visual document retrieval models
Calculate VRAM requirements for LLM models
Browse and filter ML model leaderboard data
View and submit LLM benchmark evaluations
Measure BERT model performance using WASM and WebGPU
Evaluate open LLMs in the languages of LATAM and Spain.
Convert Hugging Face models to OpenVINO format
Generate and view leaderboard for LLM evaluations
Explore and visualize diverse 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.