Automated Script Generation using Machine Learning

This project implements automated script generation using transformer-based machine learning models like GPT-2, GPT-3, and LLaMA. It fine-tunes pre-trained models on a dataset of movie scripts to generate coherent and contextually relevant dialogues.

Features

• Fine-tuning GPT-2 on a custom dataset
• Deploying the model on Hugging Face Spaces
• Exposing API for chatbot interaction
• Integrating with a React frontend

Deployment on Hugging Face Spaces

The model is deployed on Hugging Face Spaces using Gradio, which provides a user-friendly web interface for interaction. Below are the steps involved in deployment:

1. Prepare the Model:

   • Use transformers from Hugging Face to load and fine-tune GPT-2 on a dataset of movie scripts.
   • Save the trained model and tokenizer for deployment.

2. Create a Hugging Face Space:

   • Navigate to Hugging Face Spaces and create a new space.
   • Select Gradio as the application type.

3. Upload the Model and Code:

   • Push the fine-tuned model and script files to the space repository using Git.
   • Implement a Gradio interface for real-time text generation.

4. Expose the API:

   • The Gradio interface runs on server_name="0.0.0.0", server_port=7860.
   • The model API is available for integration with external applications like a React frontend.

Screenshots

Visit the Web Interface

Click the link below to interact with the AI script generator:

🔗 Hugging Face Space