GlotLID
| Property | Value |
|---|---|
| License | Apache 2.0 |
| Paper | EMNLP 2023 Paper |
| Framework | FastText |
| Supported Languages | 2102 |
What is GlotLID?
GlotLID is a state-of-the-art language identification model built using FastText architecture, specifically designed to handle an extensive range of languages, including low-resource ones. Currently in its third version (V3), it supports identification of 2102 different language labels using three-letter ISO codes with script information.
Implementation Details
The model is implemented using the FastText framework and can be easily integrated into existing workflows. It provides straightforward text classification capabilities for language identification, with particular strength in handling low-resource languages that are often overlooked in traditional language identification systems.
- Built on FastText architecture for efficient text classification
- Supports 2102 distinct language labels
- Uses three-letter ISO codes with script information
- Optimized for both high-resource and low-resource languages
Core Capabilities
- Accurate language identification across 2000+ languages
- Support for low-resource languages
- Fast and efficient processing
- Easy integration through FastText API
- Support for "zxx" and "und" series labels
Frequently Asked Questions
Q: What makes this model unique?
GlotLID stands out for its extensive language coverage, supporting over 2100 languages, including many low-resource languages that are typically not covered by other language identification models. The model's ability to handle such a wide range of languages while maintaining accuracy makes it particularly valuable for global language processing applications.
Q: What are the recommended use cases?
The model is ideal for applications requiring language identification across a broad spectrum of languages, particularly when dealing with low-resource languages. It's suitable for content filtering, document classification, multilingual text processing, and automated language-specific routing in NLP pipelines.
