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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....
| Autores principales: | , |
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| Autor Corporativo: | |
| Formato: | Video |
| Idioma: | Inglés |
| Publicado: |
[Erscheinungsort nicht ermittelbar] :
Pragmatic AI Solutions,
2021
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| Edición: | 1st edition. |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 520 | |a 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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