structured-data-models-client
One Python client for NVIDIA's structured-data foundation models. Ask a predictive question of one table, or of a whole relational schema, without training a model for each dataset.
pip install structured-data-models-client
Inference runs in a NIM, so this package downloads no weights and needs no GPU.
import pandas as pd
from sdm_client import KumoTabular, Request, SDMClient
labelled = pd.DataFrame(
{
'age': [31.0, 44.5, 28.0, 51.0, 39.0],
'spend': [120.0, 430.0, 90.0, 510.0, 260.0],
'churn': [0, 1, 0, 1, 0],
}
)
to_score = pd.DataFrame({'age': [33.0, 47.0], 'spend': [150.0, 480.0]})
request = Request(
context=labelled, predict=to_score, target='churn', task='classification'
)
with SDMClient(url='http://localhost:8000') as client:
print(client.predict(request, model=KumoTabular()).to_pandas())
The model is an argument, not a method name. For several related tables, ask in
the Predictive Query Language and pass KumoRelational() instead; that needs
pip install 'structured-data-models-client[relational]'.
Documentation, the other four packages and the examples are in the repository: https://github.com/NVIDIA/structured-data-models-client
Apache-2.0. Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES.
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Release files for structured-data-models-client 1.0.0
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