Generate and view leaderboard for LLM evaluations
Evaluate open LLMs in the languages of LATAM and Spain.
Display genomic embedding leaderboard
View and submit LLM benchmark evaluations
View and compare language model evaluations
Search for model performance across languages and benchmarks
Submit models for evaluation and view leaderboard
Explore and submit models using the LLM Leaderboard
Retrain models for new data at edge devices
Find recent high-liked Hugging Face models
Launch web-based model application
Export Hugging Face models to ONNX
Submit deepfake detection models for evaluation
Arabic MMMLU Leaderborad is a model benchmarking tool designed to evaluate and compare the performance of different large language models (LLMs) on Arabic language tasks. It provides a comprehensive leaderboard where researchers and developers can assess model capabilities across a variety of NLP tasks specific to Arabic. The platform allows for transparent and standardized evaluation, enabling the community to track progress in Arabic NLP.
What is the purpose of the Arabic MMMLU Leaderborad?
The purpose is to provide a standardized platform for evaluating and comparing LLMs on Arabic language tasks, fostering transparency and collaboration in NLP research.
How can I get started with the leaderboard?
Start by preparing your model, selecting tasks, and following the step-by-step instructions provided on the platform.
Can I customize the evaluation metrics?
Yes, the platform allows users to define and track specific evaluation metrics tailored to their needs.