Tutorials

These tutorials demonstrate how to build Data Designer configurations and execute them through the NeMo Data Designer plugin.

Configuration and Execution

Data Designer separates configuration (building dataset schemas) from execution (generating the data).

Part 1: Build Configs (Library)

Use data_designer.config to define your dataset. See the library documentation for comprehensive guides on column types, constraints, and processors.

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import data_designer.config as dd
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config_builder = dd.DataDesignerConfigBuilder(model_configs)
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config_builder.add_column(dd.SamplerColumnConfig(...))
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config_builder.add_column(dd.LLMTextColumnConfig(...))

Part 2: Execute (Plugin)

Run the configuration with the CLI or SDK:

$
nemo data-designer preview product_reviews.py --num-records 5
$
nemo data-designer create product_reviews.py --num-records 30

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import os
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from nemo_platform import NeMoPlatform
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client = NeMoPlatform(
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    base_url=os.environ.get("NMP_BASE_URL", "http://localhost:8080"),
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    workspace="default",
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)
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data_designer = client.data_designer
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preview = data_designer.preview(config_builder)
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job = data_designer.create(config_builder, num_records=1000)

Prerequisites

Complete Setup to ensure you have the NeMo Services running locally and an inference provider available. These tutorials reference the default NVIDIA Build model provider, which is created as default/nvidia-build during setup.

Tutorials