Amazon SageMaker

This guide explains how to upload models deployed in Amazon SageMaker to Openlayer.

​

Find the model artifacts in SageMaker

First, you need to find the S3 bucket that contains the model’s artifacts. You can do so by going to “Amazon SageMaker” > “Inference” > “Models”, and clicking on your model’s name.

Then, copy the “Model data location” to your clipboard.

​

Download the model artifacts

With the model data location in hand, you can use the following code, which downloads the model’s artifacts from S3, saves it to disk, and untars the downloaded file.

import boto3
import tarfile

# The AWS profile that has access to the S3 bucket
AWS_PROFILE = "your_profile"

# Information about the location of the dataset in the S3 bucket
S3_BUCKET = "bucket_name"
S3_KEY = "path/to/your/model.tar.gz" # This is what you copied from "Model data location"

OUTPUT_FILE = "model.tar.gz"

session = boto3.session.Session(
    profile_name=AWS_PROFILE
)
s3 = session.client("s3")
s3.download_file(
    Bucket=S3_BUCKET,
    Key=S3_KEY,
    Filename=OUTPUT_FILE
)

# Untar the downloaded file
tarfile.open(OUTPUT_FILE).extractall("model")

​

Upload to Openlayer

Once the model’s artifacts are saved to disk, you can proceed as usual to upload a full model to the Openlayer platform.

You can refer to the notebook examples from our examples gallery GitHub repository, to see how the model’s artifacts from various ML frameworks are used in the full model upload, and to our API reference, for details on the add_model method. You can also check our How to upload datasets and models for development guide.