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Developed by spacy
CPU-optimized Romanian natural language processing model, including tokenization, part-of-speech tagging, dependency parsing, named entity recognition, and other functions
Downloads 17
Release Time : 3/2/2022

Model Overview

This is a small Romanian processing pipeline provided by spaCy, containing complete NLP components, suitable for basic analysis tasks of Romanian text.

Model Features

CPU Optimization
Specially optimized for CPU usage scenarios, suitable for resource-constrained environments
Complete NLP Pipeline
Includes a complete processing pipeline from tokenization to named entity recognition
High-Accuracy Part-of-Speech Tagging
Part-of-speech tagging accuracy reaches 95.58%
Multitask Learning
A single model handles multiple NLP tasks simultaneously

Model Capabilities

Tokenization
Part-of-speech Tagging
Dependency Parsing
Named Entity Recognition
Lemmatization
Sentence Segmentation

Use Cases

Text Analysis
Romanian Text Processing
Basic NLP processing of Romanian text
Obtain linguistic information such as tokenization, part-of-speech tagging, and dependency relations
Information Extraction
Named Entity Recognition
Identify entities such as person names, place names, and organization names from Romanian text
F1 score reaches 71.34%
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