Display genomic embedding leaderboard
Display model benchmark results
View and submit machine learning model evaluations
Compare and rank LLMs using benchmark scores
Visualize model performance on function calling tasks
Display and filter leaderboard models
View and submit LLM benchmark evaluations
Explore GenAI model efficiency on ML.ENERGY leaderboard
Compare LLM performance across benchmarks
Push a ML model to Hugging Face Hub
Explore and submit models using the LLM Leaderboard
Analyze model errors with interactive pages
Explore and manage STM32 ML models with the STM32AI Model Zoo dashboard
DGEB is a Model Benchmarking platform designed to display genomic embedding leaderboards. It provides a comprehensive comparison of different models based on their performance in genomic embedding tasks. Users can explore and analyze the results to identify top-performing models, making it a valuable resource for researchers and developers in the field of genomics.
• Real-Time Leaderboard Updates: Stay up-to-date with the latest model performances. • Detail-Rich Comparisons: View metrics such as accuracy, computational requirements, and more. • Interactive Visualizations: Explore data through charts and graphs for better insights. • Custom Model Submission: Users can submit their own models for benchmarking. • Filter and Sort Options: Narrow down results based on specific criteria. • Model Version Tracking: Track improvements and changes across model versions.
1. What is the purpose of DGEB?
DGEB is designed to simplify the process of comparing genomic embedding models, helping researchers identify the best tools for their projects.
2. How often are the leaderboards updated?
The leaderboards are updated in real-time as new models are submitted or existing models are re-evaluated.
3. Can I submit my own custom model?
Yes, DGEB allows users to submit their own models for benchmarking. Visit the platform for submission guidelines and requirements.