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---
title: Content Summarizer
emoji: 🔥
colorFrom: purple
colorTo: green
sdk: streamlit
sdk_version: 1.17.0
app_file: app.py
pinned: false
---
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
### Content Summarizer
The Content Summarizer is a project that can generate summaries for various types of content including text, URLs, audio, video, and YouTube. It utilizes the transformers library and leverages the BART-large-CNN, T5-small and Whisper-tiny.en models to provide effective summarization.
It contains two options for summarization:
- Overall summary
- Auto-Chapters summary
#### Overall summary
The overall summary is generated using BART-large-CNN with chunk split algorithm.
#### Auto Chapters summary
In this type, the text content is split using clustering techniques and chunk split algorithm and uses BART-large-CNN and T5-small for summarization which gives blocks of summary with headings for each.
To run the app, install the packages from requirements.txt and execute the command `streamlit run app.py` from the root of this project.
This repository has also been added as a space in huggingface: https://huggingface.co/spaces/KevlarVK/content_summarizer
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