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Here are 12 open-source projects and scripts that can help summarize large text:

GPT-3: OpenAI's GPT-3 and ChatGPT French model can be fine-tuned for summarization tasks.
BERT Summarizer: Uses the BERT model for extractive summarization.
TextRank: An extractive summarization technique based on PageRank algorithm.
Sumy: A Python library for summarization that implements TextRank and LSA algorithms.
Gensim: A popular Python library for topic modeling and summarization, including TextRank implementation.
BERT Extractive Summarizer: A BERT-based extractive summarization tool.
NLTK: The Natural Language Toolkit in Python has modules for summarization.
PyTeaser: A Python implementation of the TextTeaser algorithm for extractive summarization.
SummarizeBot: An open-source summarization tool using various algorithms.
LexRank: A graph-based algorithm for extractive summarization, implemented in Python.
T5 Summarization: Google's T5 model can be fine-tuned for summarization tasks.
OpenNMT: A neural machine translation framework that can be used for summarization.
These tools and libraries offer different approaches to summarization, ranging from simple extractive methods to more complex neural network models.

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