F

Fr Core News Sm

Developed by spacy
A CPU-optimized small French natural language processing model provided by spaCy, featuring tokenization, part-of-speech tagging, dependency parsing, named entity recognition, and more.
Downloads 160
Release Time : 3/2/2022

Model Overview

This is a French processing pipeline model primarily used for basic NLP tasks in French text, including tokenization, part-of-speech tagging, dependency parsing, named entity recognition, etc. The model is optimized for CPU usage, making it suitable for lightweight application scenarios.

Model Features

CPU Optimization
Model specifically optimized for CPU usage, suitable for resource-limited environments.
Comprehensive NLP Capabilities
Provides complete NLP processing capabilities from basic tokenization to complex syntactic analysis.
High-Accuracy Part-of-Speech Tagging
Part-of-speech tagging accuracy reaches 96.18% (UPOS).
Named Entity Recognition
F1 score reaches 81.27%, capable of identifying various named entities in French text.

Model Capabilities

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

Use Cases

Text Processing
French Text Analysis
Basic NLP processing for French news, articles, etc.
Obtain structured information such as tokenization, part-of-speech tagging, and named entities.
Information Extraction
French Entity Recognition
Extract named entities such as person names, locations, and organizations from French text.
81.27% F1 score recognition accuracy.
Featured Recommended AI Models
AIbase
Empowering the Future, Your AI Solution Knowledge Base
© 2025AIbase