Datasets:

tahrirchi
/

uz-books-v2

text stringlengths 11 3.2M
. AKAREMMA PETEM LEHT EZPALAM PETEM POCOM UZBEKISTAN Kurs bo‘yicha va ishchi qo‘llanma H REGBI O‘YINIGA KIRISH Mas’ul muharrir: Rustam Nabiyev © World Rugby 74.8.9 M96 Voliyati Osushestvleniye rabot po soxranen. B bibliotechnogo fonda C Organizatsiya spravochno-poiskovogo a biblioteki WHI UGRY GROGSTA PETEM Prezid...
O‘ZBEKISTON RESPUBLIKASI AXBOROT TEXNOLOGIYALARI VA KOMMUNIKATSIYALARINI RIVOJLANTIRISH VAZIRLIGI MUHAMMAD AL-XORAZMIY NOMIDAGI TOSHKENT AXBOROT TEXNOLOGIYALARI UNIVERSITETI KIBERXAVFSIZLIK FAKULTETI Kriptologiya kafedrasi XAVFSIZ ALOQA PROTOKOLLARI fanidan 5330300-Axborot xavfsizligi (sohalar bo‘yicha) ta’lim yo‘nalis...
"S.A.Sattarov, A.A.Mustafaqulov,\nI.H.Siddikov, F.M.Yuldashev,\nO.N.Olimov\nALTERNATIV ENERGIYA\nMAN(...TRUNCATED)
"M.TOJIYEV, I.NIGMATOV\nHAYOT\nFAOLIYATI\nXAVFSIZLIGI\n68.9\nT-60\nO‘ZBEKISTON RESPUBLIKASI OLIY V(...TRUNCATED)
"O‘ZBEKISTON RESPUBLIKASI OLIY VA O‘RTA MAXSUS\nTA’LIM VAZIRLIGI\nI.B. Shukurov\nBIOLOGIK KIMY(...TRUNCATED)
"O‘ZBEKISTON RESPUBLIKASI OLIY VA\nO‘RTA MAXSUS TA’LIM VAZIRLIGI\nO‘RTA MAXSUS, KASB-HUNAR T(...TRUNCATED)
"UO‘K: 87.82-1\nKBK: 85\nI-120\n\"Istiqlolim - istiqbolim, Vatan\" (bolalar uchun she’rlar). / T(...TRUNCATED)
"N.R. YUSUPBEKOV,\nD.P. MUXITDINOV\nTEXNOLOGIK JARAYONLARNI\nMODELLASHTIRISH VA\nOPTIMALLASHTIRISH\n(...TRUNCATED)
"Husniddin Nuriddinov\nMO‘JIZAKOR\nELEMENTLAR\nRUNIN\nSTRONDLY\n107,463213\nEMBSH\nB\nBR\n137.33\n(...TRUNCATED)
"R. NORMAHMATOV\nOZIQ-OVQAT TOVARLARI\nSIFAT EKSPERTIZASI\nR. NORMAHMATOV\nOZIQ-OVQAT TOVARLARI\nSIF(...TRUNCATED)

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Dataset Card for UzBooks V2

Dataset Summary

UzBooks V2 is an improved version of the UzBooks book corpus for Uzbek language. It contains nearly 40,000 books in two splits:

Split	Description	Examples
lat	Fully Latin-transliterated version	38,339
cyr	Fully Cyrillic-transliterated version	38,339

What's New in V2?

OCR Engine Upgrade: Switched from Tesseract → Google Cloud Vision OCR
Cleaner Text: Google OCR produces far fewer recognition errors, especially for mixed-script content
Same Structure & Size: Maintains compatibility with v1 — same splits, same number of examples

Usage

from datasets import load_dataset

uz_books2 = load_dataset("tahrirchi/uz-books-v2")

# Access Latin version
print(uz_books2["lat"][0]["text"])

# Access Cyrillic version
print(uz_books2["lat"][0]["text"])

Data Fields

Field	Type	Description
`text`	`string`	Full text content of the book

Dataset Creation

Books were collected from various public sources and processed using Google Cloud Vision OCR, which delivers substantially better accuracy than Tesseract for Uzbek text — particularly in handling the coexistence of Latin and Cyrillic scripts. Then, lat and cyr splits were generated using curated transliteration scripts.

Citation

@online{Mamasaidov2024UzBooksV2,
    author    = {Mukhammadsaid Mamasaidov and Abror Shopulatov},
    title     = {UzBooks V2 dataset},
    year      = {2026},
    url       = {https://huggingface.co/datasets/tahrirchi/uz-books-v2}
}

Contacts

We believe that this work will enable and inspire all enthusiasts around the world to open the hidden beauty of low-resource languages, in particular Uzbek.

For questions or issues:

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