Display and analyze PyTorch Image Models leaderboard
Try the Hugging Face API through the playground
Explore how datasets shape classifier biases
Finance chatbot using vectara-agentic
Form for reporting the energy consumption of AI models.
Explore and submit NER models
Create detailed data reports
Generate synthetic dataset files (JSON Lines)
Need to analyze data? Let a Llama-3.1 agent do it for you!
Explore and compare LLM models through interactive leaderboards and submissions
Evaluate diversity in data sets to improve fairness
Generate images based on data
Check your progress in a Deep RL course
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.