mukhal/xlm-roberta-ner
Named Entity Recognition with Pretrained XLM-RoBERTa
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.
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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.
Stars
92
Forks
28
Language
Python
License
MIT
Category
Last pushed
Jul 30, 2021
Commits (30d)
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