SolidityBench Leaderboard
Explore GenAI model efficiency on ML.ENERGY leaderboard
Export Hugging Face models to ONNX
Evaluate adversarial robustness using generative models
Analyze model errors with interactive pages
Compare and rank LLMs using benchmark scores
Display and submit language model evaluations
Push a ML model to Hugging Face Hub
Calculate memory usage for LLM models
View and submit machine learning model evaluations
Evaluate RAG systems with visual analytics
Browse and evaluate language models
Multilingual Text Embedding Model Pruner
The SolidityBench Leaderboard is a comprehensive benchmarking platform designed to evaluate and compare the performance of language models across various tasks and datasets. It provides a standardized framework for assessing model capabilities, enabling users to identify the most suitable models for their specific needs. The leaderboard ranks models based on their accuracy, efficiency, and overall performance.
The SolidityBench Leaderboard offers a rich set of features for model benchmarking and comparison:
What is the purpose of SolidityBench Leaderboard?
The SolidityBench Leaderboard aims to provide a standardized platform for comparing language models, helping researchers and developers identify the best models for their applications.
How are models ranked on the leaderboard?
Models are ranked based on their performance across various tasks and datasets, using metrics such as accuracy, F1-score, and inference time. Higher scores indicate better performance.
Can I submit my own model to the leaderboard?
Yes, the SolidityBench Leaderboard allows users to submit their own models. Visit the submission section on the website and follow the guidelines to add your model to the benchmarking process.