# Sampling

After you are finished with modeling, your can use your synthesizer to generate and save synthetic data.

```python
 from sdv.utils import load_synthesizer

synthesizer = load_synthesizer(
    filepath='my_synthesizer.pkl'
)

synthetic_data = synthesizer.sample(num_rows=1_000_000)

# save the data as a CSV
synthetic_data.to_csv('synthetic_data.csv', index=False)
```

#### What are your sampling needs?

Single table synthesizers can support multiple sampling needs.

<table data-card-size="large" data-view="cards"><thead><tr><th></th><th></th><th data-hidden data-card-target data-type="content-ref"></th></tr></thead><tbody><tr><td><a href="sampling/sample-realistic-data"><strong>Sample Realistic Data</strong></a></td><td>Create large amounts of synthetic data that follow the same format and mathematical properties as the real data.</td><td><a href="sampling/sample-realistic-data">sample-realistic-data</a></td></tr><tr><td><a href="sampling/conditional-sampling"><strong>Sample Conditional Data</strong></a></td><td>Request specific, fixed values to appear in your data. Use this for simulating scenarios, de-biasing your data and more.</td><td><a href="sampling/conditional-sampling">conditional-sampling</a></td></tr></tbody></table>


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