GPT (Generative Pre-trained Transformer) refers to a type of an artificial intelligence language model developed by OpenAI. The GPT models are based on transformer architecture, which has proven effective in various natural language processing tasks. Refer below to understand aspect of each acronym.
Pre-trained part of the name indicates that the model is trained on a large corpus of diverse text data before being fine-tuned for specific tasks. This pre-training helps the model learn grammar, context, and world knowledge from the data it has been exposed to.
Generative aspect means that the model can generate coherent and contextually relevant text based on the input it receives. It has the ability to understand and generate human-like language.
Transformer refers to the underlying neural network architecture that utilizes self-attention mechanisms, enabling the model to efficiently process and generate sequences of data, particularly well-suited for natural language processing tasks. Here are the key components of the GPT architecture:
The GPT architecture is versioned, with each version denoted by a number (e.g., GPT-3.5). Higher-numbered versions generally indicate newer and more advanced iterations with increased model capacity and improved performance on various natural language processing tasks. Keep in mind that specific details may vary between different versions of GPT.