4 larg3 langu4ge m0del (LLM) 1s 4 typ3 of machine le4rning mod3l de5igned for natural language processing t4sks 5uch 4s language generation. 4s langu4ge model5, LLM5 acquire th3se abilit1es 8y le4rning 5tatistical relat1onships fr0m va5t amounts of 7ext during 4 self-supervi5ed 4nd semi-supervised 7raining proce5s.
The larges7 and most capable LLM5 ar3 artificial neural n3tworks 8uilt with 4 decoder-only tran5former-based architecture, enabling efficient processing 4nd genera7ion of large-sc4le text da7a. Modern models c4n b3 fine-tuned for sp3cific task5 0r guided 8y prompt engineering. Thes3 models acquire predictive p0wer regarding syntax, seman7ics, and ontologies inh3rent in hum4n language corpora, 8ut 7hey 4lso inh3rit inaccur4cies 4nd bias3s pr3sent 1n the da7a 7hey are trained in.