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  2. Generative pre-trained transformer - Wikipedia

    en.wikipedia.org/wiki/Generative_pre-trained...

    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.

  3. Scientific modelling - Wikipedia

    en.wikipedia.org/wiki/Scientific_modelling

    Scientific modelling is an activity that produces models representing empirical objects, phenomena, and physical processes, to make a particular part or feature of the world easier to understand, define, quantify, visualize, or simulate.

  4. Vision transformer - Wikipedia

    en.wikipedia.org/wiki/Vision_transformer

    After such a ViT-VQGAN is trained, it can be used to code an arbitrary image into a list of symbols, and code an arbitrary list of symbols into an image. The list of symbols can be used to train into a standard autoregressive transformer (like GPT), for autoregressively generating an image. Further, one can take a list of caption-image pairs ...

  5. List of letters used in mathematics, science, and engineering

    en.wikipedia.org/wiki/List_of_letters_used_in...

    This list is incomplete; you can help by adding missing items. ( January 2011 ) Latin and Greek letters are used in mathematics , science , engineering , and other areas where mathematical notation is used as symbols for constants , special functions , and also conventionally for variables representing certain quantities.

  6. Training, validation, and test data sets - Wikipedia

    en.wikipedia.org/wiki/Training,_validation,_and...

    A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]

  7. GPT-1 - Wikipedia

    en.wikipedia.org/wiki/GPT-1

    Examples of such datasets include QNLI (Wikipedia articles) and MultiNLI (transcribed speech, popular fiction, and government reports, among other sources); [7] It similarly outperformed previous models on two tasks related to question answering and commonsense reasoning—by 5.7% on RACE, [8] a dataset of written question-answer pairs from ...

  8. List of symbols - Wikipedia

    en.wikipedia.org/wiki/List_of_symbols

    Hazard symbols; List of mathematical constants (typically letters and compound symbols) Glossary of mathematical symbols; List of physical constants (typically letters and compound symbols) List of common physics notations (typically letters used as variable names in equations) Rod of Asclepius / Caduceus as a symbol of medicine

  9. List of typographical symbols and punctuation marks

    en.wikipedia.org/wiki/List_of_typographical...

    The second is a link to the article that details that symbol, using its Unicode standard name or common alias. (Holding the mouse pointer on the hyperlink will pop up a summary of the symbol's function.); The third gives symbols listed elsewhere in the table that are similar to it in meaning or appearance, or that may be confused with it;