[WIP] Advanced workshop covering ML Batch serving on Azure
-
Updated
Mar 15, 2021
[WIP] Advanced workshop covering ML Batch serving on Azure
Serve pytorch inference requests using batching with redis for faster performance.
We perform batch inference on lead scoring task using Pyspark.
Support Yolov5(4.0)/Yolov5(5.0)/YoloR/YoloX/Yolov4/Yolov3/CenterNet/CenterFace/RetinaFace/Classify/Unet. use darknet/libtorch/pytorch/mxnet to onnx to tensorrt
This repository provides sample codes, which enable you to learn how to use auto-ml image classification, or object detection under Azure ML(AML) environment.
Torchserve server using a YoloV5 model running on docker with GPU and static batch inference to perform production ready and real time inference.
Ray Saturday Dec 2022 edition
Support batch inference of Grounding DINO. "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"
LightGBM Inference on Datafusion
MLOps project that recommends movies to watch implementing Data Engineering and MLOps best practices.
Torchfusion is a very opinionated torch inference on datafusion.
Add a description, image, and links to the batch-inference topic page so that developers can more easily learn about it.
To associate your repository with the batch-inference topic, visit your repo's landing page and select "manage topics."