Evaluate code generation with diverse feedback types
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Submit models for evaluation and view leaderboard
Compare LLM performance across benchmarks
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Browse and submit model evaluations in LLM benchmarks
SolidityBench Leaderboard
Calculate GPU requirements for running LLMs
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Explain GPU usage for model training
ConvCodeWorld is an AI-powered platform designed to evaluate and benchmark code generation models. It allows users to test and compare the performance of different AI models by providing diverse feedback types on generated code outputs. This tool is particularly useful for developers, researchers, and organizations aiming to assess the effectiveness of code generation models in various scenarios.
• Model Benchmarking: Compare multiple code generation models based on their performance and quality of output.
• Diverse Feedback Types: Provide feedback through code reviews, bug reports, performance metrics, and user ratings to evaluate models comprehensively.
• Customizable Scenarios: Define specific coding tasks and scenarios to test models in real-world conditions.
• In-depth Analytics: Access detailed reports and insights to understand model strengths and weaknesses.
• Community Collaboration: Share feedback and results with the community to foster collaborative improvement.
What types of feedback can I provide on ConvCodeWorld?
You can provide feedback through code reviews, bug reports, performance metrics, and user ratings to evaluate models effectively.
How do I choose the right models for benchmarking?
Select models based on your specific needs, such as programming languages, task complexity, or desired output quality. ConvCodeWorld allows you to filter and compare models based on these criteria.
Is ConvCodeWorld suitable for non-developers?
Yes, ConvCodeWorld is designed to be user-friendly. While technical expertise can be helpful, the platform provides tools and guidance for users of all skill levels to evaluate code generation models.