factsumm
FactSumm: Factual Consistency Scorer for Abstractive Summarization (by Huffon)
summarizers
Package for controllable summarization (by hyunwoongko)
factsumm | summarizers | |
---|---|---|
1 | 1 | |
107 | 76 | |
- | - | |
5.8 | 0.0 | |
5 months ago | over 1 year 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.
factsumm
Posts with mentions or reviews of factsumm.
We have used some of these posts to build our list of alternatives
and similar projects.
summarizers
Posts with mentions or reviews of summarizers.
We have used some of these posts to build our list of alternatives
and similar projects.
-
[P]Summarizers: Easy to use controllable summarization package
For more information, please visit https://github.com/hyunwoongko/summarizers.
What are some alternatives?
When comparing factsumm and summarizers you can also consider the following projects:
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
bert2bert-summarization - Abstractive summarization using Bert2Bert framework.
sumy - Module for automatic summarization of text documents and HTML pages.
haystack - :mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.