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The Indic LLM Leaderboard is a tool designed to help users browse and compare Large Language Models (LLMs) specifically developed for Indic languages. It serves as a centralized platform for evaluating and understanding the capabilities of various LLMs across different Indic languages, enabling users to make informed decisions about which model best suits their needs.
• Benchmarked Models: The leaderboard features a curated list of LLMs trained on Indic languages, with their performance metrics.
• Multi-language Support: Covers a wide range of Indic languages, providing insights into model capabilities for each.
• Detailed Metrics: Includes performance scores, dataset details, and model architectures for comprehensive evaluation.
• Filter and Sort: Users can filter models based on specific languages or use cases.
• Model Comparison: Enables side-by-side comparison of multiple models to identify strengths and weaknesses.
• Regular Updates: The leaderboard is updated periodically to reflect the latest advancements in Indic LLMs.
What is the purpose of the Indic LLM Leaderboard?
The leaderboard is designed to simplify the process of selecting and comparing LLMs for Indic languages, helping users find the most suitable model for their needs.
How are the models evaluated on the leaderboard?
Models are evaluated based on benchmark tests that assess their performance on tasks such as text generation, translation, and question-answering in Indic languages.
How often is the leaderboard updated?
The leaderboard is updated periodically to include new models and reflect the latest advancements in the field of Indic language LLMs.