Remove old README.txt and add as .md with markdown

Make this clearer to run

examples/onnxruntime/resnet50/README.md

+# Resnet50 inference with MIGraphX and Onnxruntime
+
+## Description
+
+This example demonstrates how to perform an MIGraphX Python API inference through onnxruntime. The model used here is from Torchvision's pretrained resnet50 model
+
+## Content
+- [Basic Setup](#Basic-Setup)
+- [**Running this Example**](#Running-this-Example)
+
+## Basic Setup
+Before running inference we must first install MIGraphX via the Docker method as it also downloads onnxruntime into the dockerfile created.
+
+## Running this Example
+
+This directory contains everything needed to perform an inference once MIGraphX has been installed in the docker contaienr
+
+```
+$ mkdir build
+$ cd build
+$ CXX=/opt/rocm/llvm/bin/clang++ cmake ..
+$ make -j$(nproc) package
+$ dpkg -i *.deb
+```
+Once you've build and installed MIGraphX as a deb package go to the examples folder, run the pre-req script to build and install
+onnxruntime and then install the approrpaite version of pytorch
+
+```
+$ cd examples/onnxruntime/resnet50
+$ ./prereq_steps.sh
+$ pip list | grep onnxruntime
+$ python resnet50.py
+```

examples/onnxruntime/resnet50/README.txt

-/*
- * The MIT License (MIT)
- *
- * Copyright (c) 2015-2023 Advanced Micro Devices, Inc. All rights reserved.
- *
- * Permission is hereby granted, free of charge, to any person obtaining a copy
- * of this software and associated documentation files (the "Software"), to deal
- * in the Software without restriction, including without limitation the rights
- * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
- * copies of the Software, and to permit persons to whom the Software is
- * furnished to do so, subject to the following conditions:
- *
- * The above copyright notice and this permission notice shall be included in
- * all copies or substantial portions of the Software.
- *
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
- * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
- * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL THE
- * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
- * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
- * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
- * THE SOFTWARE.
- */
-
-
- To run the example please do the following:
-
-- Build and install MIGraphX as a package using "make package && dpkg -i *.deb" in the build folder via the Docker build method
-- Move to this folder examples/onnxruntime/resnet50
-- Run the prequisite install script ./prereq_steps.sh - this installs pytorch
-- The prequisite install script will also build and install onnxruntime on your system. Ensure this with pip list | grep onnxruntime
-- run the resnet50 inference via python resnet50.py
- 
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