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Ro Core News Lg

Developed by spacy
CPU-optimized Romanian language processing pipeline with complete NLP components including token classification, dependency parsing, and named entity recognition
Downloads 55
Release Time : 3/2/2022

Model Overview

Large Romanian language processing model provided by spaCy, supporting NLP tasks such as POS tagging, dependency parsing, and named entity recognition, optimized for CPU usage

Model Features

CPU Optimization
Processing pipeline specifically optimized for CPU usage scenarios, suitable for resource-limited environments
Comprehensive NLP Components
Includes complete natural language processing functionalities such as token classification, dependency parsing, named entity recognition, and lemmatization
High-quality Vectors
Contains 500,000 unique vectors (300 dimensions), providing rich semantic representations

Model Capabilities

POS tagging
Dependency parsing
Named entity recognition
Lemmatization
Sentence segmentation
Morphological feature analysis

Use Cases

Text Analysis
Romanian Text Processing
Basic NLP processing for Romanian texts including POS tagging and dependency parsing
Accuracy: POS tagging 93.95%, NER F1 score 76.11%
Information Extraction
Extract named entities (people, locations, organizations, etc.) from Romanian texts
Supports recognition of 16 entity types
Linguistic Research
Morphological Analysis
Analyze morphological features of Romanian vocabulary
Morphological feature accuracy 95.00%
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