Summarization is the task of producing a shorter version of a document while preserving its important information. Some models can extract text from the original input, while other models can generate entirely new text.

About Summarization
https://youtu.be/yHnr5Dk2zCI

Use Cases
Research Paper Summarization 🧐
Research papers can be summarized to allow researchers to spend less time selecting which articles to read. There are several approaches you can take for a task like this:

Use an existing extractive summarization model on the Hub to do inference.
Pick an existing language model trained for academic papers. This model can then be trained in a process called fine-tuning so it can solve the summarization task.
Use a sequence-to-sequence model like T5 for abstractive text summarization.
https://huggingface.co/tasks/summarization