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A large language model (LLM) is a type of machine learning model designed for natural language processing tasks such as language generation. LLMs are language models with many parameters, and are trained with self-supervised learning on a vast amount of text. The largest and most capable LLMs are generative pretrained transformers (GPTs).
A large language model (LLM) is a type of machine learning model designed for natural language processing tasks such as language generation. LLMs are language models with many parameters, and are trained with self-supervised learning on a vast amount of text. This page lists notable large language models.
Generative pre-trained transformer – Type of large language model; Large language model – Type of machine learning model; Music and artificial intelligence – Usage of artificial intelligence to generate music; Generative AI pornography – Explicit material produced by generative AI
Bag-of-words model – model that represents a text as a bag (multiset) of its words that disregards grammar and word sequence, but maintains multiplicity. This model is a commonly used to train document classifiers; Brill tagger – Cache language model – ChaSen, MeCab – provide morphological analysis and word splitting for Japanese
T5 (Text-to-Text Transfer Transformer) is a series of large language models developed by Google AI introduced in 2019. [1] [2] Like the original Transformer model, [3] T5 models are encoder-decoder Transformers, where the encoder processes the input text, and the decoder generates the output text.
It is notable for its dramatic improvement over previous state-of-the-art models, and as an early example of a large language model. As of 2020, BERT is a ubiquitous baseline in natural language processing (NLP) experiments. [3] BERT is trained by masked token prediction and next sentence prediction.
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