Webinar: How to Accelerate and Deploy YOLOv5 in 15 Minutes

In this hands-on webinar, our product manager, Amir Servi, walks you through a simple and fast way to accelerate* and deploy a YOLOv5 model (or any other deep learning model) in less than 15 minutes.

Watch now to learn how to:

  • Automate the compilation and quantization of the model with a click of a button
  • Benchmark the baseline and optimized models performance on various HW environments
  • Analyze the impact of the optimization on the performance and costs-to-serve
  • Deploy the model in production using 3 lines of code

*Accelerate – make the model run faster, and more efficiently in any production environment, thus, increasing its throughput and cutting the cost-to-serve.

Get free access to Deci’s optimization and deployment tools (RTiC and Infery) — request free trial to Deci’s deep learning platform.

You May Also Like

Webinar: How to Fine-Tune LLMs with QLoRA

Webinar: Optimizing Pose Estimation for Real-Time Performance

Webinar: How to Optimize LLMs for Production

Add Your Heading Text Here
					from transformers import AutoFeatureExtractor, AutoModelForImageClassification

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

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