pytextrank
bert2bert-summarization
pytextrank | bert2bert-summarization | |
---|---|---|
2 | 1 | |
2,102 | 30 | |
0.5% | - | |
5.9 | 0.0 | |
2 months ago | over 3 years ago | |
Python | Python | |
MIT License | Apache License 2.0 |
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pytextrank
bert2bert-summarization
-
[P] Summarization using Bert2Bert Frameworks
Here is the implementation of the Summarization model using pytorch lighting and huggingface transformers. The model used Bert2Bert, which uses the Korean Bert as an encoder-decoder structure. This model recorded ROUGE-1 score of 44.8 on the Korean benchmark dataset. Details of the implementation can be found here. (https://github.com/hyunwoongko/bert2bert-summarization)
What are some alternatives?
pke - Python Keyphrase Extraction module
sumy - Module for automatic summarization of text documents and HTML pages.
spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python
summarizers - Package for controllable summarization
spacy-models - 💫 Models for the spaCy Natural Language Processing (NLP) library
textstat - :memo: python package to calculate readability statistics of a text object - paragraphs, sentences, articles.
turing - :sparkles: :dna: Turing ES - Enterprise Search, Chatbot using Search Engine and Many NLP Vendors.
Text-Summarization-using-NLP - Text Summarization using NLP to fetch BBC News Article and summarize its text and also it includes custom article Summarization
communities - Library of community detection algorithms and visualization tools
retext-readability - plugin to check readability
zsl-kg - Framework for zero-shot learning with knowledge graphs.
sqlite-ner - sqlite tool to extract entities into a new table using spaCy