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For many years, sequence modelling and generation was done by using plain recurrent neural networks (RNNs). A well-cited early example was the Elman network (1990). In theory, the information from one token can propagate arbitrarily far down the sequence, but in practice the vanishing-gradient problem leaves the model's state at the end of a long sentence without precise, extractable ...
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).
The model architecture remains largely unchanged from that of LLaMA-1 models, but 40% more data was used to train the foundational models. [26] The accompanying preprint [26] also mentions a model with 34B parameters that might be released in the future upon satisfying safety targets. LLaMa 2 includes foundation models and models fine-tuned for ...
Model-driven architecture (MDA) is a software design approach for the development of software systems. It provides a set of guidelines for the structuring of specifications, which are expressed as models. Model Driven Architecture is a kind of domain engineering, and supports model-driven engineering of software systems.
Mamba [a] is a deep learning architecture focused on sequence modeling. It was developed by researchers from Carnegie Mellon University and Princeton University to address some limitations of transformer models, especially in processing long sequences. It is based on the Structured State Space sequence (S4) model. [2] [3] [4]
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 C4 model was created by the software architect Simon Brown between 2006 and 2011 on the roots of Unified Modelling Language (UML) and the 4+1 architectural view model. The launch of an official website under a Creative Commons license [ 3 ] and an article [ 4 ] published in 2018 popularised the emerging technique.
[[Category:Architecture templates]] to the <includeonly> section at the bottom of that page. Otherwise, add <noinclude>[[Category:Architecture templates]]</noinclude> to the end of the template code, making sure it starts on the same line as the code's last character.