GPT 2 Implementation

Authors- Rucha Bhide, Jhanvi Sandeep, Anjali Kakekar, Professor Jyoti Gaikwad

Abstract-This paper aims at implementing GPT-2, a state-of-the-art natural language processing model developed by Open AI, for multiple applications in natural language understanding and generation. GPT-2, which stands for “Generative Pre-trained Transformer 2,” is known for its ability to generate coherent and contextually relevant text, making it a powerful tool for tasks such as text generation, language translation, sentiment analysis, and more. The project involves training and fine-tuning the GPT-2 model on specific datasets to adapt it to particular tasks. The steps required in this project will be data preprocessing, model training, and hyper parameter tuning. The trained model can be used for a wide range of applications such as chat bots, content generation, translation, and text summarization. It will address the computational requirements for deploying GPT-2 in real-world applications and potential scalability challenges. In conclusion, the implementation of GPT-2 offers the opportunity to harness cutting-edge natural language processing capabilities for a multitude of applications. However, it is crucial to balance the power of this technology with ethical considerations and responsible usage, which will be a central focus of this project.

DOI: /10.61463/ijset.vol.12.issue2.167