summarizers
Package for controllable summarization (by hyunwoongko)
bert2bert-summarization
Abstractive summarization using Bert2Bert framework. (by hyunwoongko)
| summarizers | bert2bert-summarization | |
|---|---|---|
| 1 | 1 | |
| 76 | 31 | |
| - | - | |
| 0.0 | 0.0 | |
| over 1 year ago | over 3 years ago | |
| Python | Python | |
| Apache License 2.0 | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
summarizers
Posts with mentions or reviews of summarizers.
We have used some of these posts to build our list of alternatives
and similar projects.
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[P]Summarizers: Easy to use controllable summarization package
For more information, please visit https://github.com/hyunwoongko/summarizers.
bert2bert-summarization
Posts with mentions or reviews of bert2bert-summarization.
We have used some of these posts to build our list of alternatives
and similar projects.
-
[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?
When comparing summarizers and bert2bert-summarization you can also consider the following projects:
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
pytextrank - Python implementation of TextRank algorithms ("textgraphs") for phrase extraction
factsumm - FactSumm: Factual Consistency Scorer for Abstractive Summarization
sumy - Module for automatic summarization of text documents and HTML pages.