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GLiNER2.5 Multi model released for unified information extraction

By PulseAugur Editorial · [1 sources] ·

The fastino/gliner2.5-multi-v1 model, a multilingual information extraction tool, has been released on Hugging Face. This model utilizes a boundary architecture and supports various tasks including entity extraction, text classification, and relation extraction within a single schema. It is built upon the mDeBERTa-v3-base architecture and can be run locally on CPU, CUDA, or MPS, requiring Python 3.10 or newer and PyTorch. AI

IMPACT Enables more versatile and localized information extraction across multiple languages and tasks with a single model.

RANK_REASON Release of a new open-source information extraction model on Hugging Face. [lever_c_demoted from research: ic=1 ai=1.0]

Read on Hugging Face Trending Models →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

GLiNER2.5 Multi model released for unified information extraction

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Release of a new open-source information extraction model on Hugging Face. [lever_c_demoted from research: ic=1 ai=1.0]
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model release, product
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High
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22 days old
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COVERAGE [1]

  1. Hugging Face Trending Models TIER_1 Italiano(IT) · fastino ·

    fastino/gliner2.5-multi-v1

    token-classification · 11,987 downloads · 67 likes

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