mukhal/xlm-roberta-ner

Named Entity Recognition with Pretrained XLM-RoBERTa

45
/ 100
Emerging

This tool helps data scientists and NLP researchers extract key entities like names, locations, and organizations from text in various languages. You provide your raw text data, marked with the entities you want to identify, and it outputs a specialized model that can automatically find and categorize those entities in new, unseen text. It's designed for those who need to process large volumes of unstructured text to identify specific pieces of information.

No commits in the last 6 months.

Use this if you need to build a custom named entity recognition (NER) model that works effectively across multiple languages.

Not ideal if you're looking for an off-the-shelf solution for common entities in a single language without needing to train a custom model.

natural-language-processing information-extraction text-analytics multilingual-data computational-linguistics
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 9 / 25
Maturity 16 / 25
Community 20 / 25

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Stars

92

Forks

28

Language

Python

License

MIT

Last pushed

Jul 30, 2021

Commits (30d)

0

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