Generate and view leaderboard for LLM evaluations
Rank machines based on LLaMA 7B v2 benchmark results
View and submit machine learning model evaluations
Visualize model performance on function calling tasks
Upload ML model to Hugging Face Hub
View and submit language model evaluations
Evaluate and submit AI model results for Frugal AI Challenge
Text-To-Speech (TTS) Evaluation using objective metrics.
View LLM Performance Leaderboard
View and submit LLM benchmark evaluations
Calculate survival probability based on passenger details
Optimize and train foundation models using IBM's FMS
Launch web-based model application
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.