abstract = "Information extraction (IE) is fundamental to numerous NLP applications, yet existing solutions often require specialized models for different tasks or rely on computationally expensive large language models. We present GLiNER2, a unified framework that enhances the original GLiNER architecture to support named entity recognition, text classification, and hierarchical structured data extraction within a single efficient model. Built on a fine-tuned encoder architecture, GLiNER2 maintains CPU efficiency and compact size while introducing multi-task composition through an intuitive schema-based interface. Our experiments demonstrate competitive performance across diverse IE tasks with substantial improvements in deployment accessibility compared to LLM-based alternatives. We release GLiNER2 as an open-source library available through pip, complete with pre-trained models and comprehensive documentation."
他說：「既然人民越來越窮，我們將會看到新一波的社會動盪。」
。关于这个话题，91视频提供了深入分析
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1.最近一年销售收入小于5000万元（含）的企业，比例不低于5%。
，这一点在PDF资料中也有详细论述
Марк Эйдельштейн привлек внимание иностранных журналистов на модном показе14:58
Обвинения США против Ирана описали фразой «строят самолет в процессе полета»08:51，这一点在PDF资料中也有详细论述