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A reference dataset is a representative sample of the data your model was trained on (or any dataset you want to use as a baseline). Openlayer uses this dataset for tests that monitor data drift — by comparing the distribution of your live data against the reference distribution.

How to upload a reference dataset

You can upload a reference dataset to your inference pipeline with the Python SDK.

See full Python example

1

Load your dataset into a DataFrame

Your dataset should be in a format Openlayer can understand. Here’s a minimal example with a single row:
Python
2

Define the dataset configuration

The dataset config is a dictionary containing information that helps Openlayer understand your data.For example, the dataset above is from a tabular classification task, so our dataset config will have information such as the feature names, class names, and others:
Python
3

Upload the dataset to Openlayer

Now, you can upload your reference dataset alongside its config to Openlayer:
Python