How does GPT generate text?

GPT (Generative Pre-trained Transformer) generates text by predicting the next token (word or part of a word) based on the previous ones. The model is trained on a vast amount of text data, which allows it to understand the context and structure of language.

The main mechanism is the transformer, which uses attention to analyze the relationships between words in a sentence. When generating, GPT sequentially selects the most probable next token, considering the already generated text.

An example of a simplified process:

# Pseudocode for text generation
context = "Hello, how"
while not end_of_text:
    next_token = model.predict_next_token(context)
    context += next_token
    if next_token == "<end>":
        break
print(context)

Thus, GPT creates coherent and meaningful text based on probabilities and the context of previous words.