This model is trained on a dataset of historical documents related to Jim Crow laws in the United States. The model was developed by drawing on the expertise of scholars and analyzing legal texts from various states, with the goal of identifying similarities between different states' Jim Crow laws. As such, this model may be useful for researchers or policymakers interested in understanding the history of racial discrimination in the US legal system.

The easiest way to use this model locally is via the Transformers library pipelines for inference.

Once you have installed transformers, you can run the following code. This will download and cache the model locally and allow you to make predictions on text input.

from transformers import pipeline

classifier = pipeline('text-classification', "biglam/autotrain-beyond-the-books")
classifier(text)

This will return predictions in the following format: