gouwsxander/slop-detector-bert

Slop Detector

A simple model to detect AI-written content.

Model Details

This model is a PEFT of bert-base-cased.

It was trained on a dataset of scraped paragraphs from Wikipedia, as well as AI rewrites of said paragraphs.

More detail about the training data can be found here.

Usage

The basic usage is as follows:

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