seopbo/nlp_classification
Implementing nlp papers relevant to classification with PyTorch, gluonnlp
This project helps developers implement advanced text classification techniques using Korean text data. It takes raw text inputs, such as movie reviews or pairs of sentences, and processes them to output classifications like sentiment (positive/negative) or whether two sentences have the same meaning (paraphrase detection). This is for researchers or developers working on Natural Language Processing (NLP) with Korean datasets, who want to experiment with different deep learning models.
229 stars. No commits in the last 6 months.
Use this if you are an NLP developer or researcher specifically looking to apply or compare various state-of-the-art text classification models to Korean language datasets for tasks like sentiment analysis or paraphrase detection.
Not ideal if you need a plug-and-play solution for non-Korean languages or tasks outside of single-sentence and pairwise text classification, or if you are not comfortable with Python and deep learning frameworks.
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229
Forks
41
Language
Python
License
MIT
Last pushed
Dec 08, 2022
Commits (30d)
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