[Webinar] How to Ship Computer Vision Models to Production Faster with Better Performance

Fast and efficient inference plays a key role in the success of computer vision-based applications, especially when there’s a strict performance requirement such as in autonomous vehicles and IoT-enabled and mobile devices.

In most use cases, achieving real-time inference to deliver the best user experience is a must. With inference acceleration in the spotlight, join our live webinar to learn about:

  • The importance of inference performance
  • Challenges in computer vision inference
  • Factors that impact inference and how to improve them
  • Tips and best practices for accelerating inference performance

If you want to learn more about optimizing your computer vision applications, book a demo here.

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					from transformers import AutoFeatureExtractor, AutoModelForImageClassification

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

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