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Developed by spacy
A medium-sized Spanish NLP processing pipeline provided by spaCy, optimized for CPU usage, containing complete language processing components
Downloads 447
Release Time : 3/2/2022

Model Overview

This is a medium-sized Spanish natural language processing model that includes complete NLP functionalities such as tokenization, part-of-speech tagging, dependency parsing, and named entity recognition, optimized for CPU usage.

Model Features

CPU Optimization
Specifically optimized for CPU usage scenarios, suitable for running in environments without GPUs
Complete NLP Components
Includes a full natural language processing pipeline from tokenization to named entity recognition
Pre-trained Word Vectors
Includes 20,000 300-dimensional word vectors, covering 500,000 vocabulary terms
High Accuracy
Achieves an F1 score of 0.89 on NER tasks and part-of-speech tagging accuracy exceeding 0.96

Model Capabilities

Text Tokenization
Part-of-Speech Tagging
Dependency Parsing
Named Entity Recognition
Lemmatization
Sentence Segmentation
Morphological Analysis

Use Cases

Text Processing
Spanish Text Analysis
Performs grammatical analysis and structural understanding of Spanish texts
Accurately identifies parts of speech, syntactic relationships, and named entities
Information Extraction
Extracts key information from Spanish texts
Identifies entities such as person names, locations, and organization names in the text
Language Learning
Spanish Learning Assistance
Analyzes the grammatical structure of Spanish sentences
Helps learners understand sentence components and grammatical relationships
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