Awesome-LLM-Eval

Awesome-LLM-Eval

Awesome-LLM-Eval is a curated repository that provides a comprehensive list of resources for evaluating large language models (LLMs). This includes tools, datasets, benchmarks, demos, leaderboards, papers, and documentation, aimed at exploring the boundaries of generative AI technology.

Key Features:

• Curated Tools: A selection of tools specifically designed for LLM evaluation.
• Datasets and Benchmarks: Access to various datasets and benchmarks for rigorous testing.
• Demos: Live demonstrations of LLM capabilities.
• Leaderboards: Performance rankings for different LLMs based on various criteria.
• Research Papers: A collection of academic papers that discuss methodologies and findings in LLM evaluation.

Benefits:

• Comprehensive Resource: Serves as a one-stop-shop for researchers and developers interested in LLM evaluation.
• Community Driven: Contributions from various authors enhance the repository's value and relevance.
• Regular Updates: The repository is frequently updated with new tools and findings, ensuring users have access to the latest information.

Highlights:

• Sections dedicated to specific evaluation aspects such as coding ability, reasoning speed, and multimodal capabilities.
• Inclusion of popular LLMs and frameworks for training, making it easier for users to find relevant resources.

Explore the repository to enhance your understanding and evaluation of large language models!