{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/naab-a-ready-to-use-plug-and-play-corpus-for","title":"naab: A ready-to-use plug-and-play corpus for Farsi","arxiv_id":"2208.13486","date":"2022-08-29","proceeding":null,"authors":["Sadra Sabouri","Elnaz Rahmati","Soroush Gooran","Hossein Sameti"],"abstract":"The rise of large language models (LLMs) has transformed numerous natural language processing (NLP) tasks, yet their performance in low and mid-resource languages, such as Farsi, still lags behind resource-rich languages like English. To address this gap, we introduce naab, the largest publicly available, cleaned, and ready-to-use Farsi textual corpus. naab consists of 130GB of data, comprising over 250 million paragraphs and 15 billion words. Named after the Farsi word NAAB (meaning \"pure\" or \"high-grade\"), this corpus is openly accessible via Hugging Face, offering researchers a valuable resource for Farsi NLP tasks. In addition to naab, we provide naab-raw, an unprocessed version of the dataset, along with a pre-processing toolkit that allows users to clean their custom corpora. These resources empower NLP researchers and practitioners, particularly those focusing on low-resource languages, to improve the performance of LLMs in their respective domains and bridge the gap between resource-rich and resource-poor languages.","url_abs":"https://arxiv.org/abs/2208.13486v2","url_pdf":"https://arxiv.org/pdf/2208.13486v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[],"tasks":[],"methods":[],"datasets_introduced":[{"slug":"naab","name":"naab","full_name":"naab"}],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2208.13486","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}