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

# Surrogate Models

> Explore our client guide to adding surrogate models. Learn about prerequisites and key details for cases where uploading the actual model isn’t possible.

# Surrogate Models

Fiddler’s explainability features require a model on the backend that can generate explanations for you.

> 📘 If you don't want to or cannot upload your actual model file, Surrogate Models serve as a way for Fiddler to generate approximate explanations.

A surrogate model **is built automatically** when you call [`add_surrogate`](/sdk-api/python-client/connection) on an existing model that has a [baseline dataset](/developers/python-client-guides/publishing-production-data/creating-a-baseline-dataset) defined. You just need to provide a few key details on how your model operates during onboarding.

## Surrogate Model prerequisites:

* An onboarded model with:
  * A defined model task (regression, binary classification, etc.)
  * A target column (ground truth labels)
  * An output column (model predictions)
  * Model feature columns
  * A baseline dataset

### Update the artifact

```python theme={null}
DATASET_NAME = 'YOUR_DATASET_NAME'

dataset = fdl.Dataset.from_name(name=DATASET_NAME, model_id=model.id)

job = model.add_surrogate(
    dataset_id=dataset.id
)
job.wait()
```