billpku/NLP_In_Action
Do NLP tasks with some SOTA methods
This project provides practical examples for common text analysis tasks. It takes raw text as input and helps you identify key entities, categorize documents, or generate new human-like text. Anyone working with large volumes of text data, such as data scientists, researchers, or NLP practitioners, would find this useful for applying advanced techniques.
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Use this if you need concrete, executable examples to implement advanced text analysis methods like Named Entity Recognition, text classification, or text generation using models like BERT, XLNet, or GPT-2.
Not ideal if you are looking for a plug-and-play application with a graphical user interface or a solution that doesn't require coding knowledge.
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92
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Jupyter Notebook
License
MIT
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Last pushed
Jan 18, 2021
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