RajGothi / City-Inhabitant-Term-Prediction--T5-Model

To create a predictive model that, when provided with the name of a city, can generate the corresponding term used to describe its inhabitants, such as "Mumbai" -> "Mumbaikar."

Problem:

Tools:

pip install sentencepiece
pip install transformers
pip install datasets
conda install pytorch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2 pytorch-cuda=11.8 -c pytorch -c nvidia
pip install pandas
pip install numpy
pip install matplotlib
pip install tqdm
pip install beautifulsoup4
pip install requests
pip install wandb
pip install scikit-learn

Prerequisite:

GPU (Otherwise T5 model training will be very slow.) wandb "account" replace with your account in t5_train.py file.

Dataset pre-processing:

pre-processing.ipynb

Scrapping code:

1. scrap.py (use only wikipedia query)
2. google_scrap.py (Use search + wikipedia query)

Train:

Run python t5_train.py (To train the model)

Inference:

t5inference.ipynb (replace the above trained model checkpoint path in code)

PPT:

NLP_ass1_presentation.pptx contains the overview of approach,results and analysis.