Merge pull request UppuluriKalyani#760 from NANDAGOPALNG/main

Added a new project called "Text Summarizer"

Generative Models/Text Summarizer/README.md

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+# Text Summarizer
+
+A Natural Language Processing (NLP) project that uses Generative AI to summarize long pieces of text into concise, meaningful summaries.
+
+# Table of Contents
+
+**Introduction**
+
+**Features**
+
+**How it Works**
+
+**Installation**
+
+**Usage**
+
+**Example Use Cases**
+
+**Contributing**
+
+**License**
+
+## Introduction
+
+The Text Summarizer project uses Gen AI to automatically summarize long pieces of text into shorter, more digestible summaries. This can be useful for a variety of applications, such as:
+
+Summarizing news articles or blog posts
+
+Condensing long documents or reports
+
+Generating abstracts for academic papers
+
+## Features
+
+Automatic Summarization: The Text Summarizer uses Gen AI to automatically summarize text without the need for manual intervention.
+
+Customizable Summary Length: Users can specify the desired length of the summary, from a brief abstract to a longer summary.
+
+Support for Multiple File Formats: The Text Summarizer can handle text files in various formats, including .txt, .pdf, and .docx.
+
+## How it Works
+
+The Text Summarizer uses a combination of natural language processing (NLP) and machine learning algorithms to analyze the input text and generate a summary. The process involves:
+
+Text Preprocessing: The input text is preprocessed to remove stop words, punctuation, and other irrelevant information.
+
+Text Analysis: The preprocessed text is then analyzed to identify key phrases, entities, and concepts.
+
+Summary Generation: The analyzed text is then used to generate a summary, based on the user-specified summary length.
+
+## Installation
+
+To install the Text Summarizer, follow these steps:
+
+Clone the repository: git clone https://github.com/NANDAGOPALNG/ML-Nexus/tree/main/Generative%20Models/Text%20Summarizer
+
+Install the required dependencies: pip install -r requirements.txt
+
+Run the Text Summarizer: python text_summarizer.py
+
+## Usage
+
+To use the Text Summarizer, simply run the text_summarizer.py script and follow the prompts. You can specify the input text file, summary length, and other options as needed.
+
+## Example Use Cases
+
+Summarizing a news article: python text_summarizer.py -i news_article.txt -s 100
+
+Summarizing a research paper: python text_summarizer.py -i research_paper.pdf -s 200
+
+## Contributing
+
+Contributions are welcome! If you'd like to contribute to the Text Summarizer project, please fork the repository and submit a pull request.
+
+## License
+
+The Text Summarizer project is licensed under the MIT License. See LICENSE for details

Generative Models/Text Summarizer/app.py

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+import torch
+import gradio as gr
+
+# Use a pipeline as a high-level helper
+from transformers import pipeline
+
+text_summary = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6", torch_dtype=torch.bfloat16)
+
+# model_path = ("../Models/models--sshleifer--distilbart-cnn-12-6/snapshots"
+#               "/a4f8f3ea906ed274767e9906dbaede7531d660ff")
+# text_summary = pipeline("summarization", model=model_path,
+#                 torch_dtype=torch.bfloat16)
+
+
+
+# text='''Elon Reeve Musk (/ˈiːlɒn/ EE-lon; born June 28, 1971) is a businessman and investor.
+# He is the founder, chairman, CEO, and CTO of SpaceX; angel investor, CEO, product architect,
+# and former chairman of Tesla, Inc.; owner, executive chairman, and CTO of X Corp.;
+# founder of the Boring Company and xAI; co-founder of Neuralink and OpenAI; and president
+# of the Musk Foundation. He is one of the wealthiest people in the world; as of April 2024,
+# Forbes estimates his net worth to be $178 billion.[4]'''
+# print(text_summary(text));
+
+def summary (input):
+    output = text_summary(input)
+    return output[0]['summary_text']
+
+gr.close_all()
+
+# demo = gr.Interface(fn=summary, inputs="text",outputs="text")
+demo = gr.Interface(fn=summary,
+                    inputs=[gr.Textbox(label="Input text to summarize",lines=6)],
+                    outputs=[gr.Textbox(label="Summarized text",lines=4)],
+                    title="@GenAILearniverse Project 1: Text Summarizer",
+                    description="THIS APPLICATION WILL BE USED TO SUMMARIZE THE TEXT")
+demo.launch()

Generative Models/Text Summarizer/requirements.txt

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+transformers
+torch
+gradio