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OpenML: [493] Web platform with Python, R, Java, and other APIs for downloading hundreds of machine learning datasets, evaluating algorithms on datasets, and benchmarking algorithm performance against dozens of other algorithms. PMLB: [494] A large, curated repository of benchmark datasets for evaluating supervised machine learning algorithms ...
Wikipedia-based Image Text Dataset 37.5 million image-text examples with 11.5 million unique images across 108 Wikipedia languages. 11,500,000 image, caption Pretraining, image captioning 2021 [7] Srinivasan e al, Google Research Visual Genome Images and their description 108,000 images, text Image captioning 2016 [8] R. Krishna et al.
Download as PDF; Printable version; ... Pages in category "Datasets in machine learning" ... Text is available under the Creative Commons Attribution-ShareAlike 4.0 ...
Download as PDF; Printable version; ... Datasets in machine learning (1 C, 12 P) S. Statistical ... Text is available under the Creative Commons Attribution ...
Start downloading a Wikipedia database dump file such as an English Wikipedia dump. It is best to use a download manager such as GetRight so you can resume downloading the file even if your computer crashes or is shut down during the download. Download XAMPPLITE from (you must get the 1.5.0 version for it to work). Make sure to pick the file ...
Sample images from MNIST test dataset. The MNIST database (Modified National Institute of Standards and Technology database [1]) is a large database of handwritten digits that is commonly used for training various image processing systems. [2] [3] The database is also widely used for training and testing in the field of machine learning.
The Pile is an 886.03 GB diverse, open-source dataset of English text created as a training dataset for large language models (LLMs). It was constructed by EleutherAI in 2020 and publicly released on December 31 of that year. [1] [2] It is composed of 22 smaller datasets, including 14 new ones. [1]
The dataset has approximately 1.2 trillion tokens and is publicly available for download. [48] Llama 2 foundational models were trained on a data set with 2 trillion tokens. This data set was curated to remove Web sites that often disclose personal data of people. It also upsamples sources considered trustworthy. [26]