俄语通用文本语料库

本数据集旨在为俄语大语言模型训练设定新的数据标准，解决模型因数据不足导致的“知识盲区”问题。包含4.28亿条高质量俄语文本，覆盖复杂对话、专业内容生成及代码编写等多种任务类型。

该体量可支撑从零预训练百亿级参数的俄语专用LLM，或大幅扩展现有模型的上下文理解范围。与公开爬虫语料不同，本数据集经过系统性去重、语言质量过滤及隐私清洗，显著降低预训练中的噪声比例。

This dataset is designed to establish new data standards for training Russian large language models (LLMs), addressing the "knowledge blind spot" issue caused by insufficient training data. It contains 428 million high-quality Russian texts covering diverse task types including complex dialogues, professional content generation, and code writing. This scale enables pre-training of Russian-specialized LLMs with tens of billions of parameters from scratch, or greatly expands the context understanding capability of existing models. Unlike publicly available crawled corpora, this dataset has undergone systematic deduplication, language quality filtering, and privacy cleaning, significantly reducing the noise ratio during pre-training.

搜集汇总

背景与挑战

背景概述

俄语通用文本语料库旨在为俄语大语言模型训练建立新标准，包含4.28亿条高质量俄语文本，覆盖复杂对话、专业内容生成和代码编写等任务。该数据集经过系统性去重、语言质量过滤及隐私清洗，可有效支撑百亿级参数模型的预训练或扩展，显著降低训练噪声。