Gliner ITA LARGE
GLiNER is a bidirectional Transformer-based general named entity recognition model, specifically optimized for Italian.
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Release Time : 5/20/2024
Model Overview
This model is a general-purpose named entity recognition model capable of identifying various entity types in text, suitable for Italian text processing.
Model Features
Italian Optimization
A named entity recognition model specifically optimized for Italian text.
General Entity Recognition
Capable of recognizing multiple types of entities, suitable for a wide range of text analysis tasks.
Bidirectional Transformer-based
Utilizes a bidirectional Transformer architecture, providing powerful contextual understanding capabilities.
Model Capabilities
Italian text processing
Named Entity Recognition
Multi-label Classification
Use Cases
Text Analysis
Information Extraction
Extract entity information such as person names, locations, and organization names from Italian text.
Efficiently and accurately identifies key entities in text.
Natural Language Processing
Data Preprocessing
Provides entity recognition support for downstream NLP tasks (e.g., relation extraction, event detection).
Improves the efficiency and accuracy of subsequent NLP tasks.
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