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# Getting Started with {{nss_short_name}}

Get started with {{nss_short_name}} for generating private synthetic versions of sensitive tabular datasets.

## Prerequisites

Before using {{nss_short_name}}, complete the [{{platform_name}} Quickstart](../get-started/quickstart.md) to install the CLI/SDK and deploy the platform.

{{nss_short_name}} 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 the [main quickstart guide](../get-started/quickstart.md).

--8<-- "_snippets/nvidia-build-model-provider.md"

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## Using the CLI

Interact with {{nss_short_name}} using the `nemo` CLI:

```shell
# List jobs
nemo safe-synthesizer jobs list

# Create a job from a config file
nemo safe-synthesizer jobs create --input-file config.json

# Create a job with inline JSON
nemo safe-synthesizer jobs create --input-data '{"spec": {...}}'
```

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## Next Steps

Run one of the [tutorials](tutorials/index.md) to create your first synthetic dataset:

- [Safe Synthesizer 101 Tutorial](tutorials/safe-synthesizer-101.md) - A beginner-friendly introduction
- [Differential Privacy Tutorial](tutorials/differential-privacy.md) - Generate differentially-private synthetic data

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