metadata

license: mit
title: Text Summarization
sdk: streamlit
emoji: 🔥
colorFrom: blue
colorTo: purple

Summarization

This project is a machine learning pipeline for natural language processing tasks. It contains a set of scripts and modules that allow you to train and evaluate various models on your own data.

Description

This repository contains a sample code with aim to demonstrate how to train a model for text summarization. The main focus is to show a basic template on how to create a structure from which we can smoothly deploy the model as well as perform inference on the trained model.

Framework used:

PyTorch
Transformers

Project Structure

pipeline This directory contains the code for the main data pipeline.

training_pipeline.py: Code for the training pipeline.
inference_pipeline.py: Code for the inference pipeline.

steps This directory includes various steps involved in the data pipeline.

evaluation.py: Code for evaluating the model.
ingest_data.py: Code for ingesting data into the pipeline.
- preprocess.py: Data preprocessing code.
- model_train.py: Model training code.

utils This directory contains utility functions used throughout the project.
- utils.py: General utility functions.
run_pipeline.py This script is the entry point for running the entire data pipeline.
Dockerfile The Dockerfile for creating a Docker image for this project.
requirements.txt

License

This project is licensed under the MIT License - see the LICENSE file for details.