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/* Creating a text summarization in Python can be done using popular libraries like transformers, spaCy, or gensim. Here's a step-by-step guide to implementing text summarization in a Jupyter notebook: Step 1: Install Necessary Libraries First, ensure you have the required libraries installed. You can use the following commands in your Jupyter notebook: !pip install transformers !pip install torch Step 2: Import Required Libraries Import the necessary modules for text summarization. We'll use the transformers library with a pre-trained model for summarization. from transformers import pipeline Step 3: Load the Pre-Trained Model Initialize a pre-trained summarization pipeline. summarizer = pipeline("summarization") Step 4: Input the Text for Summarization Provide the text you want to summarize. text = """ Artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. Specific applications of AI include expert systems, natural language processing (NLP), speech recognition, and machine vision. AI is being used in various sectors like healthcare, finance, education, and more, to enhance efficiency and decision-making. It involves technologies such as deep learning, machine learning, and neural networks. AI has the potential to revolutionize industries, but it also raises ethical questions about privacy, bias, and accountability. """ Step 5: Generate the Summary Use the summarizer to create a summary of the provided text. summary = summarizer(text, max_length=50, min_length=25, do_sample=False) print(summary[0]['summary_text']) Step 6: Full Notebook Code Here’s the complete code for reference: # Install necessary libraries !pip install transformers !pip install torch # Import the summarization pipeline from transformers import pipeline # Initialize the summarizer summarizer = pipeline("summarization") # Input text to summarize text = """ Artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. Specific applications of AI include expert systems, natural language processing (NLP), speech recognition, and machine vision. AI is being used in various sectors like healthcare, finance, education, and more, to enhance efficiency and decision-making. It involves technologies such as deep learning, machine learning, and neural networks. AI has the potential to revolutionize industries, but it also raises ethical questions about privacy, bias, and accountability. """ # Generate and print the summary summary = summarizer(text, max_length=50, min_length=25, do_sample=False) print("Summary:") print(summary[0]['summary_text']) Output After running the code, you’ll get a concise summary of the input text. Let me know if you need further assistance or enhancements, such as summarizing longer texts or creating visual outputs! */