How to use TorchServe: Walk through an example

beginner_source/torchserve_turorial.py

@@ -0,0 +1,23 @@
+# -*- coding: utf-8 -*-
+
+"""
+Introduction to TorchServe
+==========================
+
+**Author:** `Krishna Kalyan <https://github.com/krishnakalyan3>`_
+"""
+
+#########################################################################
+# Introduction
+# ------------
+# Torchserve is an open source framework for model inference, it’s a project 
+# that’s co-developed by the Applied AI team at Meta and AWS. 
+# Torchserve is today the default way to serve PyTorch models in Sagemaker, Kubeflow, MLflow, Kserve and Vertex AI. 
+# TorchServe supports multiple backends and runtimes such as TensorRT, 
+# ONNX and its flexible design allows users to add more.
+#
+# Installation
+# ------------
+#
+# pip install torchserve or conda install torchserve
+# 

index.rst

@@ -350,6 +350,14 @@ What's new in PyTorch tutorials?
    :link: beginner/Intro_to_TorchScript_tutorial.html
    :tags: Production,TorchScript
 
+
+.. customcarditem::
+   :header: Introduction to TorchServe
+   :card_description: Introduction to TorchScript, an intermediate representation of a PyTorch model (subclass of nn.Module) that can then be run in a high-performance environment such as C++.
+   :image: _static/img/thumbnails/cropped/Introduction-to-TorchScript.png
+   :link: beginner_source/torchserve_turorial.py
+   :tags: Production,TorchServe
+
 .. customcarditem::
    :header: Loading a TorchScript Model in C++
    :card_description:  Learn how PyTorch provides to go from an existing Python model to a serialized representation that can be loaded and executed purely from C++, with no dependency on Python.