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| title: Summarizer Bart | |
| emoji: 💻 | |
| colorFrom: blue | |
| colorTo: gray | |
| sdk: streamlit | |
| sdk_version: 1.29.0 | |
| app_file: app.py | |
| pinned: false | |
| # NLP Text Analyzer | |
| This project is a Python-based Natural Language Processing (NLP) Text Analyzer that uses Streamlit for the user interface and leverages Hugging Face's `transformers` library to perform text summarization using the BART model, visualize word clouds, and display the most common words in a given text. | |
| ## Overview | |
| The NLP Text Analyzer consists of the following functionalities: | |
| - **Text Summarization**: Utilizes the BART model from Hugging Face's `transformers` library to generate a summary of the user-provided text. | |
| - **Word Cloud Generation**: Generates a word cloud visualization based on the input text. | |
| - **Most Common Words**: Displays the top 10 most common words and their frequencies in the input text. | |
| ## Libraries Used | |
| - `streamlit`: Used for building the web-based user interface. | |
| - `transformers` (from Hugging Face): Provides pre-trained models for NLP tasks. Specifically, the `BartForConditionalGeneration` and `BartTokenizer` are used for text summarization. | |
| - `nltk`: Utilized for text processing tasks like tokenization and frequency analysis. | |
| - `wordcloud`: Enables the creation of word cloud visualizations. | |
| - `matplotlib`: Used for plotting word cloud and other visualizations. | |
| ## Usage | |
| ### Setup | |
| 1. Install the necessary Python dependencies listed in `requirements.txt`. | |
| 2. Run the Streamlit app locally using the command: `streamlit run your_script.py`. | |
| ### Functionality | |
| 1. **Text Input**: Enter your text in the provided text area. | |
| 2. **Summary**: Displays a summary of the input text using the BART model. | |
| 3. **Word Cloud**: Shows a visual representation of word frequency in the input text. | |
| 4. **Most Common Words**: Provides a table showing the top 10 most common words and their frequencies. | |
| ## Collab Notebook | |
| Access the Colab notebook used for development [here](https://colab.research.google.com/drive/1Y2vv_pZ5nKXKLrXrmsSu6z8hz6ncjWOz#scrollTo=y5-24_9jLdT2). | |
| ## Acknowledgments | |
| - The project utilizes the power of Hugging Face's `transformers` library for NLP tasks. | |
| - The word cloud visualization is created using the `wordcloud` library. | |
| Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference | |