Downloading a pre-trained CIFAR-10 model and input test image
In this project, we will not develop an ML model from scratch; instead, we will use a pre-trained model to dedicate more space to the model deployment with TVM. In this recipe, we will provide information on where to download the CIFAR-10 model and a header file containing an input test image as a C-byte array, required to validate the output classification.
Getting ready
The focus of this chapter will be primarily on the use of TVM to generate code for multiple target devices. To keep the problem as simple as possible and only focus on the model deployment, we will use a pre-trained CIFAR-10 quantized model and a constant input with a known output class to validate the inference process.
How to do it…
Open the web browser and create a new Colab notebook. Then, follow the following steps to download the pre-trained CIFAR-10 model and a C header file containing the input data, with an image that can...
