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Provides classification and regression datasets in a standardized format that are accessible through a Python API. Metatext NLP: https://metatext.io/datasets web repository maintained by community, containing nearly 1000 benchmark datasets, and counting.
You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made.
RAWPED is a dataset for detection of pedestrians in the context of railways. The dataset is labeled box-wise. 26000 Images Object recognition and classification 2020 [70] [71] Tugce Toprak, Burak Belenlioglu, Burak Aydın, Cuneyt Guzelis, M. Alper Selver OSDaR23 OSDaR23 is a multi-sensory dataset for detection of objects in the context of railways.
GitHub (/ ˈ ɡ ɪ t h ʌ b /) is a proprietary developer platform that allows developers to create, store, manage, and share their code. It uses Git to provide distributed version control and GitHub itself provides access control, bug tracking, software feature requests, task management, continuous integration, and wikis for every project. [8]
Academic Torrents [1] [2] [3] [4] [5] [6] is a website which enables the sharing of research data using the BitTorrent protocol. The site was founded in November 2013 ...
On April 17, 2023, TogetherAI launched a project named RedPajama to reproduce and distribute an open source version of the LLaMA dataset. [47] 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 ...
Dumps from any Wikimedia Foundation project: dumps.wikimedia.org and the Internet Archive; English Wikipedia dumps in SQL and XML: dumps.wikimedia.org /enwiki / and the Internet Archive. Download the data dump using a BitTorrent client (torrenting has many benefits and reduces server load, saving bandwidth costs).
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]