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# Getting Started with NeMo Safe Synthesizer

<a id="nss-getting-started" />

Get started with NeMo Safe Synthesizer for generating private synthetic versions of sensitive tabular datasets on a host GPU.

## Prerequisites

Before using NeMo Safe Synthesizer, complete [Setup](/documentation/get-started) to install the CLI/SDK.

NeMo Safe Synthesizer has the following additional requirements:

* An NVIDIA GPU **on the host machine** with 80GB+ VRAM (check with `nvidia-smi`). This is separate from any GPU inside a NIM container; Safe Synthesizer training runs directly on the host.
* Sufficient disk space for generated datasets (50GB+ recommended)

For general platform troubleshooting (port conflicts, health checks, and so on), refer to [Setup](/documentation/get-started).

`nemo setup` pre-configures a `default/nvidia-build` model provider during local startup.
This provider routes inference requests to models hosted on `build.nvidia.com` using the API base URL `https://integrate.api.nvidia.com`
and the NGC API key with `Public API Endpoints` permissions provided during deployment.

You can verify this provider exists by running `nemo inference providers list --workspace default`.

The tutorials in these docs use this provider for inference, but you can alternatively create your own and use it instead.

***

## Host-local CLI

For GPU development on your machine, install the Safe Synthesizer plugin from this repository and use `nemo safe-synthesizer run-local` (see [Local and Subprocess Execution](/documentation/synthesize-safe-data/about/local-and-subprocess-execution)):

```shell
BOOTSTRAP_LOCAL_PLUGIN_DIRS=plugins/nemo-safe-synthesizer make bootstrap-python
uv run nemo safe-synthesizer runtime setup
uv run nemo safe-synthesizer run-local \
  --spec-file ./nss-job.json \
  --data-source ./input.csv \
  --output-dir ./nss-output
```

The `run-local` command launches the Safe Synthesizer task in a separate runtime Python subprocess. The `nemo safe-synthesizer` CLI today exposes **run-local** and **runtime** only; platform job submission uses the Jobs API or SDK.

***

## Next Steps

Create your first synthetic dataset:

* [Safe Synthesizer 101 Tutorial](/documentation/synthesize-safe-data/tutorials/safe-synthesizer-101) - a beginner-friendly introduction
* [Local and Subprocess Execution](/documentation/synthesize-safe-data/about/local-and-subprocess-execution) - local CLI and runtime task details
* [SDK Resources](/documentation/synthesize-safe-data/sdk-resources) - Python SDK methods for jobs, builders, logs, and results

***