Hardware-Aware Model Development

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Hardware-aware model development takes into consideration the inference hardware very early in the development stage, particularly, during model selection. Also known as hardware in a loop development approach, it considers the hardware the AI models are going to be deployed on, the most suitable software stack for the target hardware, and the limitations.

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					from transformers import AutoFeatureExtractor, AutoModelForImageClassification

extractor = AutoFeatureExtractor.from_pretrained("microsoft/resnet-50")

model = AutoModelForImageClassification.from_pretrained("microsoft/resnet-50")