Text2Text Generator with HuggingFace-Model

This project demonstrates a text-to-text generation application using FastAPI, Docker, and Hugging Face. The deployed application is live and uses the google/flan-t5-small model for text generation.

Features

• FastAPI Backend: A lightweight, efficient, and easy-to-use Python framework for serving the application.
• Hugging Face Model: Utilizes the google/flan-t5-small model for generating responses based on input text.
• Dockerized Deployment: The application is containerized for portability and ease of deployment.
• Deployed on Hugging Face Spaces: Available online for demonstration.

Links

• Docker Hub Repository: arpitkadam/text2text-generator
• Deployed Application: Text2Text Generator on Hugging Face Spaces

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Getting Started

Clone the Repository

To clone the repository, use the following command:

git clone https://github.com/ArpitKadam/text2text-generator-with-HuggingFace-Model.git
cd text2text-generator-with-HuggingFace-Model

Build and Run with Docker

Build the Docker Image

docker build -t arpitkadam/text2text-generator .

Run the Docker Container

docker run -p 7860:7860 arpitkadam/text2text-generator

Pull the Prebuilt Docker Image

To pull the prebuilt image from Docker Hub:

docker pull arpitkadam/text2text-generator

Run the container:

docker run -p 7860:7860 arpitkadam/text2text-generator

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Application Details

Hugging Face Model

The application uses the Hugging Face model google/flan-t5-small. This model is a lightweight variant of the T5 (Text-to-Text Transfer Transformer) family, designed for various text generation tasks.

Steps to Use the Model

1. Install Transformers: Ensure the transformers library is installed:

   pip install transformers

2. Load the Model: Use the following Python code to load the model and perform text generation:

   from transformers import pipeline
   
   # Load the model
   pipe = pipeline("text2text-generation", model="google/flan-t5-small")
   
   # Generate text
   input_text = "Explain the importance of Docker in DevOps."
   output = pipe(input_text)
   
   print(output[0]['generated_text'])

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Project Structure

text2text-generator/
├── app.py                # FastAPI application
├── Dockerfile            # Docker configuration
├── requirements.txt      # Python dependencies
├── templates/            # HTML templates
└── .gitignore            # Files to ignore in version control

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Requirements

Ensure the following are installed:

• Python 3.9+
• Docker

Install project dependencies locally using:

pip install -r requirements.txt

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Contributions

Feel free to fork the repository and submit pull requests for improvements or bug fixes.

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License

This project is licensed under the MIT License. See the LICENSE file for details.