Deploying an Object Detection Model with Nvidia Triton Inference Server

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This tutorial will show how to deploy Object Detection Model using NVIDIA Inference Server end to end in a few easy steps.

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Topics that are covered in this video:
1. Introduction to NVIDIA NGC Catalog
2. NVIDIA NGC collection and its use cases
3. DLI Credits Giveaway Contest. 5 lucky winners will be announced after the video crossing 100K view mark.
4. What is Nvidia Triton Inference Server?
5. System Requirements
6. Docker Installation
7. NGC Setup
8. Nvidia Triton Inference Server Setup
9. Test the Model
10. Thank You Note

NVIDIA Triton™ Inference Server simplifies the deployment of AI models at scale in production. Open-source inference serving software, it lets teams deploy trained AI models from any framework (TensorFlow, NVIDIA® TensorRT®, PyTorch, ONNX Runtime, or custom) from local storage or cloud platform on any GPU- or CPU-based infrastructure (cloud, data center, or edge).

The NGC™ catalog is a hub of GPU-optimized AI, high-performance computing (HPC), and data analytics software that simplifies and accelerates end-to-end workflows. With enterprise-grade containers, pre-trained AI models, and industry-specific SDKs that can be deployed on premises, in the cloud, or at the edge, enterprises can build best-in-class solutions and deliver business value faster than ever before.

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hi, how can we do similar for deploying opensource huggingface models on titron?

amritwt