GPT-2 Output Detector

The GPT-2 Output Detector is an online tool that utilizes a machine learning model to determine the credibility of text inputs. It is built upon the RoBERTa model, which was developed by HuggingFace and OpenAI, and is implemented using the /Transformers library. By entering text into a designated box, users can receive a prediction regarding the authenticity of the input, along with corresponding probabilities. For optimal results, it is recommended to input a minimum of 50 tokens. The GPT-2 Output Detector is a valuable resource for swiftly and accurately identifying potentially fraudulent or counterfeit text inputs. Its applications span various domains, including verifying the legitimacy of news articles and filtering out spam.