GPT models are artificial intelligence models designed to generate and understand human-like text. They use deep learning to process language and perform tasks like writing and conversation.
The training data for GPT models can contain biases that may influence the generated outputs. To address this, developers use techniques like bias detection, data augmentation, and fine-tuning to minimize biases and improve model performance.
Yes, GPT (Generative Pre-trained Transformer) models can be fine-tuned to generate text in a specific narrative or storytelling structure. By providing the model with relevant training data and adjusting the parameters during fine-tuning, it can learn to mimic a certain style or tone of writing. This allows for the creation of cohesive and engaging narratives tailored to a particular genre or theme.
