Example LLM: GPT-2

Overview

Generative Pre-trained Transformer 2 (GPT-2) is an LM developed by OpenAI. It’s a successor to the original GPT model and is part of the transformer architecture. GPT-2 is known for its remarkable language generation capabilities, and it gained attention due to its ability to produce coherent and contextually relevant text.

OpenAI initially introduced GPT-2 in a research paper published in June 2019 titled “Language Models are Few-Shot Learners.” The paper outlined the architecture and capabilities of GPT-2, showcasing its ability to generate high-quality text and perform various natural language processing tasks.

Note: We are introducing an earlier iteration of GPT for use in upcoming lessons. We have chosen this specific version to ensure compatibility with our platform, optimizing its integration for a seamless learning experience.

Versions of GPT-2

GPT-2 comes in various versions, distinguished by the number of parameters (model size). Here are four versions of GPT-2, listed by the number of parameters.

Small model

The small version of GPT-2, equipped with 117 million parameters, was designed to cater to applications with limited computational resources. Despite its smaller size, this model showcases impressive language generation capabilities. Released in stages starting with smaller models, it’s a practical choice for tasks that don’t require extensive computational power.

Medium model

The medium-sized GPT-2 model boasts 345 million parameters, balancing model complexity and computational requirements. Offering enhanced performance compared to the small model, it’s an intermediary choice suitable for a range of natural language processing tasks. Like its smaller counterpart, it was released in stages. ...