The general architecture of LLM transformer models -

A pre-trained large language model (LLM) transformer is a machine learning algorithm that uses a transformer architecture to process large amounts of text data and understand natural language:

What it is
A pre-trained LLM transformer is a deep learning model that uses a transformer architecture to understand the relationships between words and phrases in a sequence of text.

How it works
The transformer architecture uses a set of neural networks, including an encoder and a decoder, to process entire sequences of text in parallel. This allows LLMs to learn basic grammar, languages, and knowledge.

What it can do
LLMs can predict the next word in a sentence and generate human-like text based on input.

Examples
GPT (Generative Pre-trained Transformer) is a type of LLM that was first introduced in 2018 by OpenAI.
Other examples include Vicuna 33B, an open source LLM derived from Llama, and EinsteinGPT, a task-specific GPT for CRM developed by Salesforce.

How to use
The transformers package provides access to many different pretrained LLMs, including GPT-2.