Datasets

MINDS-14 is a dataset designed for the intent detection task with spoken data. It encompasses 14 distinct intents extracted from a commercial system in the e-banking domain.

LongBench is a comprehensive benchmark for multilingual and multi-task purposes, with the goal to fully measure and evaluate the ability of pre-trained language models to understand long text.

MNIST is used to train and evaluate image classification models in complex tasks.

FashionMNIST is a perfect alternative dataset to MNIST in evaluating machine learning algorithms.

NIH Chest X-Ray is a large dataset containing chest X-ray images of patients collected by the National Institutes of Health (NIH) of the United States.

Cifar-100 is used to train and evaluate image classification models in complex tasks.

Cifar-10 is an important resource in the field of image recognition and classification, used to train and test machine learning models and neural networks.