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""" | |
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 checks how well models handle safety challenges β 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 = """ | |
## Submit Your Model | |
To add your model to the GuardBench leaderboard: | |
Run your evaluation using the GuardBench framework at https://github.com/whitecircle-ai/guard-bench | |
Upload your run results in .jsonl format using this form. | |
Once validated, your model will appear on the leaderboard. | |
### βοΈβ¨ Ready? Upload your results below! | |
""" | |
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}} | |
} | |
""" | |