Explore and compare LLM models through interactive leaderboards and submissions
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Create a detailed report from a dataset
Analyze and visualize data with various statistical methods
World warming land sites
Explore tradeoffs between privacy and fairness in machine learning models
Evaluate model predictions and update leaderboard
Display server status information
Make RAG evaluation dataset. 100% compatible to AutoRAG
Migrate datasets from GitHub or Kaggle to Hugging Face Hub
The Open Japanese LLM Leaderboard is a comprehensive tool designed to explore and compare large language models (LLMs), with a specific focus on Japanese language support. It provides an interactive platform to evaluate and benchmark different LLMs, helping researchers, developers, and users understand their capabilities and performance.
What is the purpose of the Open Japanese LLM Leaderboard?
The leaderboard aims to provide a transparent and standardized way to compare and evaluate large language models, particularly those focused on Japanese language tasks.
How often is the leaderboard updated?
The leaderboard is regularly updated with new models and benchmark results to reflect the latest advancements in LLM development.
Can I submit a model that does not support Japanese?
While the leaderboard specializes in Japanese language models, submissions of non-Japanese models are accepted but may not be fully optimized for the platform's focus areas.