{"id":24520441,"url":"https://github.com/martinp95/text_summarization_with_t5forconditionalgeneration","last_synced_at":"2026-05-18T06:05:42.104Z","repository":{"id":272588243,"uuid":"914354740","full_name":"martinp95/text_summarization_with_T5ForConditionalGeneration","owner":"martinp95","description":"The Text Summarization Project aims to develop an abstractive summarization model using the T5 architecture, fine-tuned on the California state bill subset of the BillSum dataset. 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The primary goal is to create a tool that can efficiently summarize lengthy texts from newsletters and other sources, providing concise and informative summaries.\n\nKey features:\n- Upload a text file for summarization.\n- Input custom text and generate summaries in real-time.\n\n## Installation\n\n1. Clone the repository:\n    ```sh\n    git clone https://github.com/martinp95/text_summarization_with_T5ForConditionalGeneration.git\n    cd text_summarization_with_T5ForConditionalGeneration\n    ```\n\n2. Create and activate the Conda environment:\n    ```sh\n    conda env create -f environment.yml\n    conda activate text_summarization_with_T5ForConditionalGeneration\n    ```\n\n## Usage\n### Step 1: Fine-Tune the Model\nTo fine-tune the model, use the Jupyter notebook `train_model.ipynb`. This notebook walks you through the steps of training the T5 model on the desired dataset.\n\n1. Open the notebook\n\n2. Execute the cells sequentially to fine-tune the model.\n\n3. Save the fine-tune model in the `fine_tuned/` direcotry\n\n### Step 2: Run the Application\nOnce the model is fine-tuned and saved, you can launch the Streamlit application:\n\n1. Start the application:\n```sh\ncd ./src/\nstreamlit run app.py\n```\n\n2. Open the local URL displayed in the terminal in your browser.\n![Summarization APP](/images/text_summarization_application.png)\n\n### Step 3: Using the Application\n* Upload a Text File: Upload a `.txt` file containing the text you want to summarize.\n![Uploaded File Summarization](/images/upload_file_summarization.png)\n\n* Manual Text Input: Use the input field to type or parte text directly\n![Manual Text Summarization](/images/manually_input_summarize.png)\n\n## License\nThis project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmartinp95%2Ftext_summarization_with_t5forconditionalgeneration","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmartinp95%2Ftext_summarization_with_t5forconditionalgeneration","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmartinp95%2Ftext_summarization_with_t5forconditionalgeneration/lists"}