A library for easily evaluating machine learning models and datasets.
With a single line of code, you get access to dozens of evaluation methods for different domains (NLP, Computer Vision, Reinforcement Learning, and more!). Be it on your local machine or in a distributed training setup, you can evaluate your models in a consistent and reproducible way! All evaluation methods come with an interactive widget to try it out directly in the browser and a documentation card that documents its use and limitations (see for example BLEU).
Learn the basics and become familiar with loading, computing, and saving with 🤗 Evaluate. Start here if you are using 🤗 Evaluate for the first time!
Practical guides to help you achieve a specific goal. Take a look at these guides to learn how to use 🤗 Evaluate to solve real-world problems.
High-level explanations for building a better understanding of important topics such as considerations going into evaluating a model or dataset and the difference between metrics, measurements, and comparisons.
Technical descriptions of how 🤗 Evaluate classes and methods work.