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Capella was created by Thales in 2007, and has been under continuous development and evolution since then. The objective is to contribute to the transformation of engineering, providing an engineering environment which approach is based on models rather than focused on documents, piloted by a process, and offering, by construction, ways to ensure effective co-engineering.
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).
Llama (Large Language Model Meta AI, formerly stylized as LLaMA) is a family of large language models (LLMs) released by Meta AI starting in February 2023. [2] [3] The latest version is Llama 3.3, released in December 2024. [4] Llama models are trained at different parameter sizes, ranging between 1B and 405B. [5]
Copilot utilizes the Microsoft Prometheus model. According to Microsoft, this uses a component called the Orchestrator, which iteratively generates search queries, to combine the Bing search index and results [86] with OpenAI's GPT-4, [87] [88] GPT-4 Turbo, [89] and GPT-4o [90] foundational large language models, which have been fine-tuned ...
Commercial. Free education edition, subscription model Java MagicDraw: No Magic, a Dassault Systèmes company Windows, Windows Server, Linux, Mac OS X (Java SE 11-compatible) [12] 1998 2022-07-01 (2022x) [13] No Commercial Java Microsoft Visio: Microsoft: Windows 1992 2016 (v16.0) No Commercial Unknown Modelio: Modeliosoft (SOFTEAM Group)
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]
Archi is a free and open-source visual-modelling and design tool for creating ArchiMate models and modelling sketches. Archi was initially funded between 2010 and 2012 by Jisc as part of a national project aimed at supporting a programme of Enterprise Architecture in the UK higher education sector.
Like earlier seq2seq models, the original transformer model used an encoder-decoder architecture. The encoder consists of encoding layers that process all the input tokens together one layer after another, while the decoder consists of decoding layers that iteratively process the encoder's output and the decoder's output tokens so far.
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