Amazon SageMaker

Deploy Nori in your AWS account from one AWS Marketplace product. One endpoint serves all three models; select the model in each client request.

Included models

`model`	Weights	Outputs	Memory policy
`nori-6m`	6M	mean, median, quantiles, full distribution	supported
`nori-30m`	30M	mean, median, quantiles, full distribution	supported
`nori-30m-thinking-medium`	30M with a medium thinking budget	mean	not supported

There is no primary or default model. Keep the same endpoint and change model= to select another model.

Before you deploy

Your AWS account must be allowed to subscribe to Marketplace products.
Request SageMaker real-time endpoint quota for ml.g5.xlarge in the region where you will deploy Nori.
Use an AWS role or profile that can create SageMaker models and endpoints.

Deploy from AWS Marketplace

Subscribe to Synthefy Nori

Open the Synthefy Nori listing in AWS Marketplace and choose View purchase options.

Synthefy Nori product page in AWS Marketplace with View purchase options

Review the pricing and terms, then choose Subscribe.

Launch the subscribed package

Option 1 — AWS Marketplace: after subscribing, choose Launch your software.

AWS Marketplace subscription page with Launch your software highlighted

Option 2 — SageMaker console: open Inference → Marketplace model packages, select the subscribed Synthefy Nori package version, choose Create model, and select a SageMaker execution role.

Create one real-time endpoint

From the Marketplace launch page, select Amazon SageMaker AI console, choose your region and Create real-time inference endpoint, then choose Create endpoint.

AWS Marketplace launch page configured for a SageMaker real-time inference endpoint

If you used option two, create the endpoint from the SageMaker model. Choose ml.g5.xlarge, set the initial instance count, and wait until the endpoint status is InService.

Invoke the endpoint

Install the Synthefy client with AWS support:

pip install "synthefy[aws]>=6.3.0"

Use the endpoint name from step three:

nori_sagemaker.py

from synthefy import SynthefyNoriClient

X_train = [[0.0, 1.0], [1.0, 0.0], [0.5, 0.5], [0.2, 0.8]]
y_train = [0.1, 0.9, 0.5, 0.3]
X_test = [[0.3, 0.7], [0.8, 0.2]]

with SynthefyNoriClient(
    mode="sagemaker",
    model="nori-30m",
    endpoint_name="your-nori-endpoint",
    region_name="us-east-1",
) as client:
    predictions = client.predict(X_train, y_train, X_test)

print(predictions)

The client uses your configured AWS role or profile. To run another included model, change model= and keep the same endpoint name. For DataFrames, categorical encoding, output types, and retries, see the Python Client guide. Requests are limited to 25 MB.

Get Started

Guides

Integration

Included models

Before you deploy

Deploy from AWS Marketplace

Invoke the endpoint

Next steps

Python Client

Nori Quickstart

​Included models

​Before you deploy

​Deploy from AWS Marketplace

​Invoke the endpoint

​Next steps

Python Client

Nori Quickstart

Included models

Before you deploy

Deploy from AWS Marketplace

Invoke the endpoint

Next steps