

# Medical Summary Generation with T5-Small

This project involves a T5-Small model for generating medical summaries from input text. 
The model is trained to understand medical data and produce concise and informative summaries.

## Table of Contents

- [Introduction](#introduction)
- [Usage](#usage)
- [Model Details](#model-details)
- [Contact](#contact)


## Introduction

The T5-Small Medical Summary Generator is built using the Hugging Face Transformers library and is designed to generate medical summaries from input text. This README provides information on how to use the model, details about the architecture, and where to find downloads.

## Usage

To use the model for medical summary generation, follow these steps:

Install the required dependencies:
   
   - pip install transformers
   - pip install torch
   - pip install datasets
   - pip install sentencepiece

## Model-details

Model Name: T5-Small Medical Summary Generator
Task: Medical Summary Generation
Architecture: T5-Small
Training Data: Details about the medical dataset used for training
Training Duration: Number of training steps, training time, etc.

## Contact
For any inquiries or support related to this model, feel free to contact:

Name   : Mahalingam Balasubramanian

Email  : mahalingamb.1978@gmail.com


{"dataset": ["medical_data"], "task": ["summarization"]}
transformers safetensors t5 text2text-generation autotrain_compatible endpoints_compatible text-generation-inference region:us