CAMeL-Lab/CAMeLBERT

Code and models for "The Interplay of Variant, Size, and Task Type in Arabic Pre-trained Language Models". EACL 2021, WANLP.

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Emerging

This project offers pre-trained language models specifically designed for Arabic text. It takes raw Arabic text and can identify sentiments (positive/negative), determine the dialect, classify poetry, recognize named entities like people or places, and tag parts of speech. The models are ideal for linguists, researchers, or anyone working with large volumes of Arabic language data who needs to automatically categorize or extract information from text.

No commits in the last 6 months.

Use this if you need to perform advanced text analysis tasks on Arabic language content, such as understanding opinions, identifying geographic origins of text, or automating data extraction.

Not ideal if your primary need is for languages other than Arabic, or if you require a simple keyword search tool instead of a sophisticated linguistic analysis system.

Arabic-NLP sentiment-analysis dialect-identification named-entity-recognition part-of-speech-tagging
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 8 / 25
Maturity 16 / 25
Community 18 / 25

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Stars

55

Forks

13

Language

Python

License

MIT

Last pushed

Jun 21, 2024

Commits (30d)

0

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