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BookCorpus was chosen as a training dataset partly because the long passages of continuous text helped the model learn to handle long-range information. [6] It contained over 7,000 unpublished fiction books from various genres.
John Berkey (August 13, 1932 – April 29, 2008) was an American artist known for his space and science fiction themed works. Some of Berkey's best-known work includes much of the original poster art for the Star Wars trilogy, the poster for the 1976 remake of King Kong and also the "Old Elvis Stamp".
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.
In deep learning, fine-tuning is an approach to transfer learning in which the parameters of a pre-trained neural network model are trained on new data. [1] Fine-tuning can be done on the entire neural network, or on only a subset of its layers, in which case the layers that are not being fine-tuned are "frozen" (i.e., not changed during backpropagation). [2]
The naming convention for these models often reflects the specific ViT architecture used. For instance, "ViT-L/14" means a "vision transformer large" (compared to other models in the same series) with a patch size of 14, meaning that the image is divided into 14-by-14 pixel patches before being processed by the transformer.
The Encyclopedia of Fantasy and Science Fiction Art Techniques is a book focused on developing artistic concepts and techniques in the fantasy genre. [1] It was authored by John Grant and Ron Tiner, [2] and published by Titan Books in 1996. David Atkinson reviewed the work for Arcane magazine, rating it an 8 out of 10 overall. [1]
A foundation model, also known as large X model (LxM), is a machine learning or deep learning model that is trained on vast datasets so it can be applied across a wide range of use cases. [1] Generative AI applications like Large Language Models are often examples of foundation models.
Since its inception, researchers in the field have raised philosophical and ethical arguments about the nature of the human mind and the consequences of creating artificial beings with human-like intelligence; these issues have previously been explored by myth, fiction and philosophy since antiquity. [23]