> ## Documentation Index
> Fetch the complete documentation index at: https://documentation.rebase.energy/llms.txt
> Use this file to discover all available pages before exploring further.

# Sweeps

> Run pipelines

{/*
Inspired by: 
https://modal.com/docs/guide/scale
*/}

## Introduction to sweeps

In many several, you might find yourself having to define parameters
for a function that are not yet know unknown or even inherently uncertain.
In these cases, it is usually beneficial (instead of guessing their value) to
parametrize and run the function for several parameter choices to examine the
impact on the output. Some common use cases for sweeps are:

* Running hyperparameter optimization search for training a machine learning model
* Running a sensitivity analysis of a simulation using multiple input scenarios
* Running an evaluation to benchmark multiple models against the same objective

## Defining and running sweeps

```python
from rebase.pipelines import pipeline

@pipeline
def function(a, b, c): 
    ...

params = [{"a": 1, "b": 2, "c": 3}]

rb.sweep(function, params)

```