GPT-Live-1.1 system card
GPT-Live-1.1 system card
GPT-Live-1.1 and GPT-Live-1.1 Quip are trained on a diverse dataset including public internet information, third-party collaboration data, and user-generated content, employing advanced data filtering processes to reduce personal information and using secure classifiers to prevent harmful content. The performance metric comparison value is based on the latest version data of published models.
2. Model Data and Training
Like OpenAI’s other models, GPT-Live-1.1 and GPT-Live-1.1 Quip were trained on diverse datasets, including information that is publicly available on the internet, information that we partner with third parties to access, and information that our users or human trainers and researchers provide or generate. Our data processing pipeline includes rigorous filtering to maintain data quality and mitigate potential risks. We use advanced data filtering processes to reduce personal information from training data. We also employ safety classifiers to help prevent or reduce the use of harmful or sensitive content, including explicit materials such as sexual content involving a minor.
Note that comparison values from previously launched models are from the latest versions of those models, so may vary slightly from values published at launch for those models.1
3.1 Voice-Native Evaluations for Disallowed Content
Source: OpenAI Deployment Safety · deploymentsafety.openai.com