SolidityBench Leaderboard
Compare audio representation models using benchmark results
Push a ML model to Hugging Face Hub
Determine GPU requirements for large language models
Run benchmarks on prediction models
Teach, test, evaluate language models with MTEB Arena
Retrain models for new data at edge devices
Browse and submit model evaluations in LLM benchmarks
Explore and submit models using the LLM Leaderboard
Explore and manage STM32 ML models with the STM32AI Model Zoo dashboard
View and submit LLM evaluations
Display leaderboard of language model evaluations
Upload a machine learning model to Hugging Face Hub
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.