Video

Webinar: How to Achieve FP32 Accuracy with INT8 Inference Speed

Watch Deci’s experts, Ofer Baratz and Borys Tymchenko, PhD, in this hands-on technical session about INT8 quantization.

✅ Learn the different quantization techniques and best practices for accelerating speed without degrading your models’ accuracy.

✅ Check out code examples and tools that you can easily leverage to achieve your inference performance targets.

Do you want to accelerate the inference of your deep learning use case? 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")