• api: call api using request lib
• data: data received from vSDS team
• data_creation: data created for matching (functional) problem, text2table problem
• data_prepare: prepared data after prompting and before training
• demo: demo the system before deploying
• deploy: building docker image for deploying on GPU environment
• deploy_support: prepare for deploy (load model)
• process: process raw data from folder "data"
• prompt: generate data using GPT api

Order to view and follow:

• generate data: data -> process -> prompt -> data_prepare -> data_creation
• call api: api
• system view: demo -> deploy, deploy_support

• data: data for training Text2Table model
• output: output of training process
• text2table: python file for training Text2Table model
• matching: run each .ipynb in drive for training
• file Text2TableTraining.ipynb: run all in kaggle for training.