Browse and submit language model benchmarks
Open Persian LLM Leaderboard
View RL Benchmark Reports
View and submit language model evaluations
View LLM Performance Leaderboard
Convert PaddleOCR models to ONNX format
Demo of the new, massively multilingual leaderboard
Display and filter leaderboard models
Visualize model performance on function calling tasks
Merge machine learning models using a YAML configuration file
Explain GPU usage for model training
Find recent high-liked Hugging Face models
Display benchmark results
The HHEM Leaderboard is a platform designed for model benchmarking, allowing users to browse and submit language model benchmarks. It serves as a centralized hub for comparing the performance of various language models across different tasks and datasets. The leaderboard provides a transparent and standardized way to track advancements in language model capabilities.
What does HHEM stand for?
HHEM stands for Human-Human Empirical Metrics, focusing on evaluating language models based on human-like performance benchmarks.
Can I submit my own language model benchmarks?
Yes, HHEM Leaderboard allows users to submit benchmarks for their own language models, provided they follow the submission guidelines and criteria.
How often are the benchmarks updated?
The benchmarks are updated regularly as new models are submitted or as existing models are re-evaluated with updated metrics.