Display and submit language model evaluations
Visualize model performance on function calling tasks
Benchmark AI models by comparison
Display and filter leaderboard models
Compare model weights and visualize differences
Browse and evaluate ML tasks in MLIP Arena
Explain GPU usage for model training
Evaluate code generation with diverse feedback types
Browse and submit model evaluations in LLM benchmarks
Browse and submit language model benchmarks
Merge machine learning models using a YAML configuration file
Browse and filter ML model leaderboard data
Merge Lora adapters with a base model
Leaderboard is a platform designed for model benchmarking, allowing users to display and submit language model evaluations. It serves as a centralized tool for comparing and tracking the performance of different AI models, providing insights into their capabilities and improvements over time.
What is the purpose of Leaderboard?
Leaderboard is a tool for benchmarking language models, enabling users to compare and track model performance in a structured manner.
How do I submit my model's evaluation?
To submit your model's evaluation, follow the guidelines provided on the platform, ensuring your data is in the correct format and includes all required metrics.
What are the benefits of using Leaderboard?
Using Leaderboard allows you to gain insights into your model's performance, identify areas for improvement, and benchmark against industry standards and other models.