Generate and view leaderboard for LLM evaluations
View and compare language model evaluations
Measure BERT model performance using WASM and WebGPU
Measure over-refusal in LLMs using OR-Bench
Launch web-based model application
View RL Benchmark Reports
Display leaderboard of language model evaluations
Evaluate LLM over-refusal rates with OR-Bench
Measure execution times of BERT models using WebGPU and WASM
Push a ML model to Hugging Face Hub
Leaderboard of information retrieval models in French
Load AI models and prepare your space
Create demo spaces for models on Hugging Face
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.