View and submit machine learning model evaluations
Browse and filter machine learning models by category and modality
Export Hugging Face models to ONNX
View RL Benchmark Reports
Create demo spaces for models on Hugging Face
Launch web-based model application
View and submit LLM benchmark evaluations
Visualize model performance on function calling tasks
Multilingual Text Embedding Model Pruner
Compare and rank LLMs using benchmark scores
Convert a Stable Diffusion XL checkpoint to Diffusers and open a PR
Display leaderboard for earthquake intent classification models
Browse and submit LLM evaluations
The LLM Safety Leaderboard is a platform designed to evaluate and compare the safety performance of large language models (LLMs). It provides a community-driven space where users can submit evaluations of machine learning models, focusing on their adherence to safety guidelines and ethical standards. The leaderboard serves as a transparent tool for developers, researchers, and users to assess and improve the safety of AI models.
1. What makes the LLM Safety Leaderboard unique?
The leaderboard's focus on safety metrics and its community-driven submissions set it apart from other model benchmarking tools. It prioritizes ethical AI development and user participation.
2. Can anyone submit a model evaluation?
Yes, any user can submit evaluations, provided they meet the platform's guidelines and quality standards. This ensures diverse and reliable data.
3. How are models ranked on the leaderboard?
Models are ranked based on aggregated safety metrics, including user submissions and automated evaluations. Rankings are updated in real-time as new data is added.