Sharing both practical insights and theoretical knowledge about LLM evaluation that we gathered while managing the Open LLM Leaderboard and designing lighteval!
The main features of huggingface/evaluation-guidebook are: Model Evaluation.
Open-source alternatives to huggingface/evaluation-guidebook include: sjwhitworth/golearn — GoLearn is a machine learning library for the Go programming language. It provides a supervised learning framework and… nvidia/isaac-gr00t. ageron/handson-ml — This is a machine learning educational repository consisting of a collection of notebooks and code examples. It… alibaba-damo-academy/medevalkit — MedEvalKit: A Unified Medical Evaluation Framework. confident-ai/deepeval — Deepeval is a framework for testing and evaluating large language model applications. It provides a suite of tools for… cluebenchmark/supercluelyb — SuperCLUE琅琊榜：中文通用大模型匿名对战评价基准.
GoLearn is a machine learning library for the Go programming language. It provides a supervised learning framework and a toolkit for building, training, and evaluating predictive models through a standardized interface. The project implements a data frame system that loads CSV files into structured grids for matrix operations. It includes a preprocessing library for discretizing continuous variables and a model evaluation toolkit that utilizes confusion matrices and cross-validation to measure precision and recall. The library covers data engineering and management, including the ability to
This is a machine learning educational repository consisting of a collection of notebooks and code examples. It provides practical implementations of diverse machine learning algorithms and workflows, ranging from traditional scientific computing to deep learning. The project features specific implementations of Scikit-Learn models, such as decision trees, random forests, and support vector machines, as well as TensorFlow examples for building neural networks, convolutional layers, and recurrent architectures. It also includes tutorials on reinforcement learning development and the creation o
MedEvalKit: A Unified Medical Evaluation Framework
