🧠 TeGenX: Lightweight Text Generation Web App

TeGenX is a lightweight, browser-based text generation application built with Streamlit. It enables users to generate English and Persian text using various pre-trained language models from Hugging Face. The app is designed for simplicity, speed, and flexibility, making it suitable for both experimentation and quick content generation.

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🚀 Features

Multilingual Support: Generate text in English and Persian.

Model Selection: Choose from various pre-trained models based on your requirements.

Interactive Interface: User-friendly Streamlit interface for seamless interaction.

Customizable Parameters: Adjust generation parameters like temperature, top-k, and top-p.

• Interactive web interface using Streamlit

• Support for multiple language models:

• English: EleutherAI/gpt-neo-125m, distilgpt2, gpt2-medium

• Persian: HooshvareLab/gpt2-fa

• Customizable generation parameters

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🧠 Available Models

Model	Size	Description	Usage
EleutherAI/gpt-neo-125m	~500MB	Lightweight GPT-Neo model	Fast inference
distilgpt2	~300MB	Distilled GPT-2	Low-resource systems
gpt2-medium	~1.5GB	Medium GPT-2	High quality generation
HooshvareLab/gpt2-fa	~485MB	Persian GPT-2 model	Persian text generation

English Models

1. EleutherAI/gpt-neo-125m

Size: ~500MB

Description: A lightweight GPT-Neo model suitable for general English text generation.

Usage: Ideal for applications requiring faster inference with reasonable performance.

2. distilgpt2

Size: ~300MB

Description: A distilled version of GPT-2, offering a balance between speed and performance.

Usage: Suitable for applications where computational resources are limited.

3.gpt2-medium

Size: ~1.5GB

Description: A medium-sized GPT-2 model providing improved performance over smaller variants.

Usage: Recommended for applications requiring higher quality text generation.

Persian Model

HooshvareLab/gpt2-fa

Size: ~485MB

Description: A GPT-2 model fine-tuned for Persian language text generation.

Usage: Best suited for generating coherent Persian text.

Download: Available on Hugging Face

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🛠 Installation

1.Clone the Repository

git clone https://github.com/yourusername/tegenx.git
cd tegenx

2.Create a Virtual Environment

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3.Install Dependencies

pip install -r requirements.txt

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#🎮 Usage

Run the Application

streamlit run app.py

2.Interact with the Interface

• Enter your prompt in the input box.

• Select the desired model for text generation.

• View the generated text displayed below.

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📁 Model Management

All models are automatically downloaded and cached by Hugging Face's Transformers library upon first use. Ensure you have a stable internet connection during the initial download.

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📝 Notes

• Performance: Larger models like gpt2-medium may require more memory and computational power.

• Customization: You can modify generation parameters in the code to better suit your application's needs.

• Extensibility: The application is designed to be easily extendable with additional models or features.