Display genomic embedding leaderboard
View and submit LLM benchmark evaluations
Measure over-refusal in LLMs using OR-Bench
View NSQL Scores for Models
Open Persian LLM Leaderboard
Convert Stable Diffusion checkpoint to Diffusers and open a PR
View and submit LLM benchmark evaluations
Find and download models from Hugging Face
Convert Hugging Face model repo to Safetensors
Launch web-based model application
Merge machine learning models using a YAML configuration file
Calculate GPU requirements for running LLMs
Evaluate reward models for math reasoning
DGEB is a model benchmarking tool designed to display genomic embedding leaderboards. It provides a centralized platform to evaluate and compare the performance of different models in genomic embedding tasks. DGEB helps researchers and developers assess how well their models handle genomic data and identify areas for improvement.
• Real-time leaderboard updates to track model performance
• Detailed accuracy metrics for comprehensive evaluation
• Visualizations to compare model performance side-by-side
• Support for multiple model architectures
• Filtering options to focus on specific datasets or metrics
• API access for seamless integration with custom workflows
What is the purpose of DGEB?
DGEB is designed to benchmark and compare the performance of models in genomic embedding tasks, helping users identify the best-performing models for their needs.
How often is the leaderboard updated?
The leaderboard is updated regularly to reflect the latest model submissions and performance metrics.
Can I submit my own model to DGEB?
Yes, DGEB typically allows users to submit their models for evaluation. Check the platform’s documentation for specific requirements and submission guidelines.