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The Ultimate Guide to Inference Acceleration of Deep Learning-Based Applications

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With deep learning models becoming more prevalent not only in academia and research but also in industry applications, there is a need to focus not only on training and reaching the desired accuracy but also on overall inference performance and cost efficiency.

In this guide, you’ll gain a deeper understanding of deep learning inference, explore different ways to improve inference performance, learn from various industry use cases, and discover actionable tips that you can apply to your existing applications.

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					from transformers import AutoFeatureExtractor, AutoModelForImageClassification

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

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