Open Persian LLM Leaderboard
Explore and submit models using the LLM Leaderboard
Retrain models for new data at edge devices
Evaluate model predictions with TruLens
Compare and rank LLMs using benchmark scores
Benchmark models using PyTorch and OpenVINO
Teach, test, evaluate language models with MTEB Arena
Browse and submit model evaluations in LLM benchmarks
Multilingual Text Embedding Model Pruner
Browse and submit LLM evaluations
Upload a machine learning model to Hugging Face Hub
Convert a Stable Diffusion XL checkpoint to Diffusers and open a PR
Measure over-refusal in LLMs using OR-Bench
The Open Persian LLM Leaderboard is a comprehensive platform designed to benchmark and evaluate Persian language models. It provides a detailed comparison of various models based on their performance on diverse Persian language tasks. The leaderboard aims to promote transparency and advance research in Persian natural language processing by offering standardized metrics and rankings.
• Model Performance Tracking: Compare the performance of different Persian language models across various tasks.
• Task-Specific Benchmarks: Evaluate models on text classification, machine translation, summarization, and more.
• Standardized Metrics: Access clear and consistent evaluation metrics for fair comparison.
• Community Contributions: Submit your own models or datasets to the leaderboard.
• Regular Updates: Stay informed with the latest developments in Persian NLP through frequent leaderboard updates.
What models are included in the Open Persian LLM Leaderboard?
The leaderboard includes a variety of Persian language models, ranging from small-scale models to state-of-the-art architectures. It also features community-submitted models.
How often is the leaderboard updated?
The leaderboard is updated regularly to reflect new models, datasets, and advancements in Persian NLP. Users are encouraged to check back frequently for the latest rankings.
Can I submit my own model to the leaderboard?
Yes, the Open Persian LLM Leaderboard is open to community contributions. Visit the platform's documentation to learn about submission guidelines and requirements.