Display benchmark results
Multilingual Text Embedding Model Pruner
Find recent high-liked Hugging Face models
Search for model performance across languages and benchmarks
Create demo spaces for models on Hugging Face
Find and download models from Hugging Face
Explore and submit models using the LLM Leaderboard
Display model benchmark results
Measure BERT model performance using WASM and WebGPU
Display and filter leaderboard models
Compare code model performance on benchmarks
GIFT-Eval: A Benchmark for General Time Series Forecasting
Browse and submit LLM evaluations
Redteaming Resistance Leaderboard is a benchmarking tool designed to evaluate the performance of AI models under adversarial attacks. It provides a platform to test and compare the resistance of different models to red teaming strategies, helping researchers and developers identify strengths and weaknesses in their systems.
• Leaderboard System: Displays rankings of models based on their resistance to adversarial attacks.
• Benchmarking Metrics: Provides detailed metrics on model performance under various red teaming scenarios.
• Customizable Attacks: Allows users to define and test specific types of adversarial inputs.
• Result Visualization: Offers graphical representations of benchmark results for easier analysis.
• Performance Tracking: Enables tracking of model improvements over time.
• Scenario Customization: Supports testing against real-world and hypothetical adversarial scenarios.
1. What does "red teaming" mean in this context?
Red teaming refers to the process of attacking a system (in this case, an AI model) to test its resistance and identify vulnerabilities.
2. How do I interpret the benchmark results?
Benchmark results show how well your model performs under adversarial conditions. Lower scores indicate weaker resistance, while higher scores suggest better robustness.
3. Can I test custom adversarial scenarios?
Yes, the leaderboard allows users to define and test custom adversarial scenarios, providing flexibility for specific use cases.