from transformers import pipeline

classifier = pipeline("text-classification", model="gouwsxander/slop-detector-bert")

inputs: str | list[str] | dict[str, str] | list[dict[str, str]] = ...
results = classifier(inputs)

Texts with label LABEL_1 are estimated to be produced by an AI.

You may get a warning about weights being initialized, but these can be ignored.

Limitations

512 token context window
Trained one paragraph at a time
Only trained on Wikipedia-style text
Only trained on AI data generated by GPT 5 Nano