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MLOps workflow with Github Actions /
Get started with MLOps and Github Actions to package a container with an ONNX model that does live inferencing with a Flask application. By using Azure ML, learn how to download the large ONNX model into the Github Action workflow, package it as a container and then push it to a container registry....
| Auteurs principaux: | , |
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| Collectivité auteur: | |
| Format: | Vidéo |
| Langue: | Inglés |
| Publié: |
[Erscheinungsort nicht ermittelbar] :
Pragmatic AI Solutions,
2021
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| Édition: | 1st edition. |
| Accès en ligne: | Texto completo (Requiere registro previo con correo institucional) |
| Résumé: | Get started with MLOps and Github Actions to package a container with an ONNX model that does live inferencing with a Flask application. By using Azure ML, learn how to download the large ONNX model into the Github Action workflow, package it as a container and then push it to a container registry. For reference use the https://github.com/alfredodeza/flask-roberta repository Topics include: * Create a container that does live inferencing with Flask and the ONNX runtime * Package the model and verify it works locally * Setup a Github Action to authenticate to Azure ML and download a previously registered model * Build the new container as a Github Action, authenticate to Docker Hub or Github Packages * Push the new container to the Github registry or any other registry like Docker Hub. |
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| Description: | Online resource; Title from title screen (viewed March 5, 2021). |
| Description matérielle: | 1 online resource (1 video file, circa 1 hr., 6 min.) |