| """ | |
| Text content for the GuardBench Leaderboard. | |
| """ | |
| TITLE = """ | |
| <div style="text-align: center; margin-bottom: 1rem"> | |
| <h1>GuardBench Leaderboard</h1> | |
| </div> | |
| """ | |
| INTRODUCTION_TEXT = """ | |
| ## Introduction | |
| GuardBench is a comprehensive benchmark for evaluating the safety guardrails of large language models (LLMs). | |
| This leaderboard tracks model performance across various safety categories, including harmful content detection, | |
| jailbreak resistance, and more. | |
| Models are evaluated on their ability to properly refuse harmful requests and detect problematic content | |
| across multiple categories and test scenarios. | |
| """ | |
| LLM_BENCHMARKS_TEXT = """ | |
| ## GuardBench evaluation methodology | |
| GuardBench checks how well models handle safety challenges — from misinformation and self-harm to sexual content and corruption. | |
| Models are tested with regular and adversarial prompts to see if they can avoid saying harmful things. | |
| We track how accurate they are, how often they make mistakes, and how fast they respond. | |
| """ | |
| EVALUATION_QUEUE_TEXT = """ | |
| ## Submission Process | |
| To submit your model results to the GuardBench leaderboard: | |
| 1. Evaluate your model using the [GuardBench framework](https://github.com/huggingface/guard-bench) | |
| 2. Format your results as a JSONL file according to our schema | |
| 3. Submit your results using the submission form with your authorized token | |
| Results will be processed and added to the leaderboard once validated. | |
| """ | |
| CITATION_BUTTON_LABEL = "Cite GuardBench" | |
| CITATION_BUTTON_TEXT = """ | |
| @misc{guardbench2023, | |
| author = {GuardBench Team}, | |
| title = {GuardBench: Comprehensive Benchmark for LLM Safety Guardrails}, | |
| year = {2023}, | |
| publisher = {GitHub}, | |
| journal = {GitHub repository}, | |
| howpublished = {\\url{https://github.com/huggingface/guard-bench}} | |
| } | |
| """ | |