Display genomic embedding leaderboard
Predict customer churn based on input details
Quantize a model for faster inference
Multilingual Text Embedding Model Pruner
Merge Lora adapters with a base model
Evaluate open LLMs in the languages of LATAM and Spain.
Compare and rank LLMs using benchmark scores
Evaluate code generation with diverse feedback types
View and submit LLM benchmark evaluations
Browse and submit model evaluations in LLM benchmarks
Upload ML model to Hugging Face Hub
Create and manage ML pipelines with ZenML Dashboard
Determine GPU requirements for large language models
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.