sagemaker inference toolkit online with Winfy

We have hosted the application sagemaker inference toolkit in order to run this application in our online workstations with Wine or directly.

Quick description about sagemaker inference toolkit:

Serve machine learning models within a Docker container using Amazon SageMaker. Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. Once you have a trained model, you can include it in a Docker container that runs your inference code. A container provides an effectively isolated environment, ensuring a consistent runtime regardless of where the container is deployed. Containerizing your model and code enables fast and reliable deployment of your model. The SageMaker Inference Toolkit implements a model serving stack and can be easily added to any Docker container, making it deployable to SageMaker. This library's serving stack is built on Multi Model Server, and it can serve your own models or those you trained on SageMaker using machine learning frameworks with native SageMaker support.

Features:

• This library's serving stack is built on Multi Model Server
• Serve your own models or those you trained on SageMaker using machine learning frameworks with native SageMaker support
• If you use a prebuilt SageMaker Docker image for inference, this library may already be included
• Implement a handler service that is executed by the model server
• Implement a serving entrypoint, which starts the model server
• This library is licensed under the Apache 2.0 License

Programming Language: Python.
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