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This repository contains a collection of hands-on labs and experiments from my Natural Language Processing (NLP) module. Each lab focuses on a specific aspect of NLP, ranging from text preprocessing and rule-based methods to advanced deep learning techniques like RNNs, LSTMs, and Transformers.
This project explores the power of Transformers for creative text generation using the GPT-2 large language model. It leverages pre-trained models to produce coherent and engaging text continuations based on user-provided prompts.
A personalized autocomplete (next word prediction) project using three different architectures: stacked LSTMs, Seq2Seq with Attention and LSTMs and GPT-2, written from scratch.
Sentimaster is an AI-powered web tool that analyzes restaurant reviews. It uses a fine-tuned GPT-2 model to classify sentiment, giving businesses real-time insights for better service and decision-making.
A GPT-2 model trained on tweets, equipped with a FastAPI endpoint, deployed using Kubernetes cluster with a k8 hosted MongoDB server and k8 Cronjob for routine tweeting.