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Generative Pre-trained Transformer 3 (GPT-3) is a large language model released by OpenAI in 2020.. Like its predecessor, GPT-2, it is a decoder-only [2] transformer model of deep neural network, which supersedes recurrence and convolution-based architectures with a technique known as "attention". [3]
Similarly, an image model prompted with the text "a photo of a CEO" might disproportionately generate images of white male CEOs, [112] if trained on a racially biased data set. A number of methods for mitigating bias have been attempted, such as altering input prompts [113] and reweighting training data. [114]
A large language model (LLM) is a type of machine learning model designed for natural language processing tasks such as language generation.As language models, LLMs acquire these abilities by learning statistical relationships from vast amounts of text during a self-supervised and semi-supervised training process.
Better not use < big > big text </ big >, unless < small > it's < big > within </ big > small </ small > text. Better not use big text , unless it's within small text. To prevent two words from becoming separated by a linewrap (e.g. Mr. Smith or 400 km/h ) a non-breaking space , sometimes also called a "non-printing character", may be used ...
Generative pretraining (GP) was a long-established concept in machine learning applications. [16] [17] It was originally used as a form of semi-supervised learning, as the model is trained first on an unlabelled dataset (pretraining step) by learning to generate datapoints in the dataset, and then it is trained to classify a labelled dataset.
The sentence "The most merciful thing in the world, I think, is the inability of the human mind to correlate all its contents", in Zalgo textZalgo text is generated by excessively adding various diacritical marks in the form of Unicode combining characters to the letters in a string of digital text. [4]