This repository contains two Jupyter Notebooks demonstrating the use of GPT models for different NLP tasks. These notebooks were developed as part of a course assignment in Deep Learning and Natural Language Processing.

Description: This notebook focuses on language modeling using GPT. It involves training a GPT model on a custom dataset to perform language modeling tasks. The notebook includes data preprocessing, model training, and evaluation of the model's performance.

Key Sections:

• Data Loading and Preprocessing
• Model Definition
• Training the GPT Model
• Evaluating the Language Model
• Generating Text with the Trained Model

Description: This notebook addresses the problem of spam detection using a GPT-2 model. It involves fine-tuning a pre-trained GPT-2 model on a spam detection dataset. The notebook includes steps for data preparation, model fine-tuning, and evaluation of the model's ability to classify spam and non-spam messages.

Key Sections:

• Data Preparation
• Fine-tuning GPT-2 for Spam Detection
• Model Evaluation
• Predicting Spam Messages