https://github.com/ts-azure-services/mlflow-pytorch-simple-example

A simple example of a locally trained PyTorch model, which is registered and used to create a real-time endpoint in Azure ML.
https://github.com/ts-azure-services/mlflow-pytorch-simple-example

azure-ml mlflow pytorch

Last synced: 7 months ago
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A simple example of a locally trained PyTorch model, which is registered and used to create a real-time endpoint in Azure ML.

• Host: GitHub
• URL: https://github.com/ts-azure-services/mlflow-pytorch-simple-example
• Owner: ts-azure-services
• License: mit
• Created: 2023-01-26T02:45:02.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2023-01-26T03:34:55.000Z (over 2 years ago)
• Last Synced: 2025-01-28T23:29:43.474Z (8 months ago)
• Topics: azure-ml, mlflow, pytorch
• Language: Python
• Homepage:
• Size: 86.9 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# mlflow-pytorch-simple-example

A simple example of a locally trained PyTorch model, which is registered and used to create a real-time

endpoint in Azure ML. The end goal is to have a real-time endpoint in Azure ML for inferencing. A sample view

of the final state is shown below.

![real-time-endpoint](./endpoint.png)

## Steps

- Ensure you have a file called `sub.env` in the root with `SUB_ID=`.

- Follow the steps in the `Makefile` to reproduce a similar outcome.