0101011/analitika
Testing Automatic Text Summarization
This project helps data scientists and researchers prepare raw text articles for natural language processing tasks. It takes in raw text data, tokenizes and filters it, and can enrich it with pre-trained word embeddings, outputting cleaned and augmented data in HDF5 and pickle formats. It's designed for someone who needs to process large collections of text for analysis or model training.
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Use this if you need to quickly pre-process a dataset of text articles for further analysis or machine learning, and want to incorporate pre-trained embeddings and data augmentation.
Not ideal if you're looking for a complete, end-to-end text summarization solution or a user-friendly interface for non-technical users.
Stars
17
Forks
2
Language
Python
License
MIT
Category
Last pushed
Aug 20, 2024
Commits (30d)
0
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