Open Persian LLM Leaderboard
Convert PyTorch models to waifu2x-ios format
Evaluate reward models for math reasoning
View and submit LLM benchmark evaluations
Search for model performance across languages and benchmarks
Analyze model errors with interactive pages
Calculate memory needed to train AI models
View RL Benchmark Reports
Merge Lora adapters with a base model
Track, rank and evaluate open LLMs and chatbots
Display leaderboard of language model evaluations
Calculate memory usage for LLM models
Determine GPU requirements for large language models
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.