Display and analyze PyTorch Image Models leaderboard
View and compare pass@k metrics for AI models
Analyze data to generate a comprehensive profile report
Explore how datasets shape classifier biases
Generate benchmark plots for text generation models
Explore tradeoffs between privacy and fairness in machine learning models
Evaluate model predictions and update leaderboard
Generate a data profile report
Browse and filter AI model evaluation results
Generate financial charts from stock data
Visualize amino acid changes in protein sequences interactively
Embed and use ZeroEval for evaluation tasks
Open Agent Leaderboard
The timm Leaderboard is a data visualization tool designed to display and analyze PyTorch Image Models. It provides a centralized platform to track, compare, and evaluate the performance of various image models, helping users make informed decisions and optimize their workflows.
• Model Comparison: Easily compare different image models based on their performance metrics.
• Real-Time Updates: Stay up-to-date with the latest model benchmarks.
• Interactive Charts: Visualize performance data through interactive and customizable charts.
• Filtering Options: Narrow down models by specific criteria such as dataset, architecture, or year.
• Detailed Metrics: Access in-depth metrics like accuracy, inference speed, and memory usage.
• Customizable Views: Tailor the leaderboard to focus on the metrics that matter most to you.
What is The timm Leaderboard used for?
The timm Leaderboard is used to display and analyze the performance of PyTorch image models, enabling users to compare and evaluate different models effectively.
How do I update the leaderboard with new models?
New models are automatically added to the leaderboard as they are released and benchmarked. You can also manually submit models for inclusion.
Is The timm Leaderboard free to use?
Yes, The timm Leaderboard is free to use, making it accessible to researchers, developers, and enthusiasts.