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| title: Text Summarizer | |
| emoji: 🏢 | |
| colorFrom: gray | |
| colorTo: gray | |
| sdk: gradio | |
| sdk_version: 5.5.0 | |
| app_file: app.py | |
| pinned: false | |
| license: apache-2.0 | |
| # Text Summarization App | |
| This is a simple app that uses the `facebook/bart-large-cnn` model from Hugging Face to summarize long-form text. The app takes an article, paper, or book, and summarizes it into key points or a concise paragraph. | |
| ## Features | |
| - Summarizes long text into a short, readable summary. | |
| - Works on various kinds of text (articles, papers, books). | |
| - Uses Hugging Face's BART model for high-quality summaries. | |
| - Provides a simple and user-friendly interface built with Gradio. | |
| ## How It Works | |
| 1. The user inputs a long-form text (article, paper, or book) in the provided input box. | |
| 2. The app processes the input using the `facebook/bart-large-cnn` model. | |
| 3. A summarized version of the text is displayed as output. | |
| ## Technologies Used | |
| - **Gradio**: For the user interface. | |
| - **Hugging Face Transformers**: For using the pre-trained BART model for summarization. | |
| - **PyTorch**: Deep learning framework used for running the BART model. | |
| ## Example | |
| Input: "Long article text here..." | |
| Output: "Concise summary of the article here..." | |
| ## License | |
| This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details. | |
| Check out the configuration reference at https://huggingface.co./docs/hub/spaces-config-reference | |