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Openlid V2

Developed by laurievb
OpenLID-v2 is a high-coverage, high-performance language identification model supporting 200 language variants, an improved version of OpenLID.
Downloads 273
Release Time : 11/12/2024

Model Overview

OpenLID-v2 is a text classification model specifically designed for language identification tasks. It can accurately identify 200 language variants, suitable for multilingual text processing environments.

Model Features

High-coverage language support
Supports 200 language variants, including many low-resource languages.
High performance
Excellent performance on the FLORES+ benchmark with a macro-average F1 score of 0.93.
Standardized preprocessing
Provides text cleaning and normalization tools that significantly improve identification accuracy.
Open-source dataset
Training data and model are fully open-source, facilitating research and improvements.

Model Capabilities

Text language identification
Multilingual text classification
Low-resource language support

Use Cases

Multilingual text processing
Social media content analysis
Identify languages in social media posts for content categorization and analysis.
Can accurately identify 200 language variants
Multilingual search engine
Provide language identification for search engines to enhance multilingual search experience.
Low misidentification rate (0.033% false positive rate)
Language data filtering
Filter specific language content from large-scale multilingual datasets.
High accuracy (macro-average F1 0.93)
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