---
title: urchade/gliner_large-v2.1
description: GLiNER is a Named Entity Recognition (NER) model capable of identifying any entity type using a bidirectional transformer encoder (BERT-like. DeBERTa, 435M parameters.
canonical_url: https://superlinked.com/models/urchade-gliner_large-v2-1
last_updated: 2026-05-25
---

# urchade/gliner_large-v2.1

GLiNER is a Named Entity Recognition (NER) model capable of identifying any entity type using a bidirectional transformer encoder (BERT-like). It provides a practical alternative to traditional NER models, which are limited to predefined entities, and Large Language Models (LLMs) that, despite th...

Source: [urchade/gliner_large-v2.1 on HuggingFace](https://huggingface.co/urchade/gliner_large-v2.1)

## Overview

| Field | Value |
|-------|-------|
| Architecture | DeBERTa |
| Parameters | 435M |
| Tasks | Extract |
| Outputs | Entities |
| License | apache-2.0 |
| Inputs | text |
| Languages | multilingual |

## Benchmarks

### CoNLL-2003

Domain: news · Task: ner · Language: en

Named entity recognition on Reuters newswire text

Corpus: 3,453 · Queries: 3,453

**Quality:** f1: 0.5483 · precision: 0.4747 · recall: 0.6487

[Reference](https://aclanthology.org/W03-0419/)