Update the Readme file

Added references to how the ONNX model file was created. Added reference to the datasource used in training. Also, have a link to how the ONNX file can be converted into an Axon model.

README.md

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 license: mit
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+A simple single label classification model, ResNet18, to predict whether the provided image is a cat or a dog.  The model was created in Fast.ai
+and exported to ONNX using PyTorch's ONNX export capabilities.  
+
+The source dataset is the OXFORD-IIIT PET.  Omkar M Parkhi, Andrea Vedaldi, Andrew Zisserman and C. V. Jawahar
+We have created a 37 category pet dataset with roughly 200 images for each class.
+The images have a large variations in scale, pose and lighting. All images havean
+associated ground truth annotation of breed, head ROI, and pixel level trimap segmentation.
+ 
+The ONNX model can be used in other frameworks like Elixir's Axon.  An example of converting the ONNX model into Axon can be found at:
+https://github.com/elixir-nx/axon/tree/main/notebooks/onnx_to_axon.livemd.