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T5 (Text-to-Text Transfer Transformer) is a series of large language models developed by Google AI introduced in 2019. [1] [2] Like the original Transformer model, [3] T5 models are encoder-decoder Transformers, where the encoder processes the input text, and the decoder generates the output text.
In natural language processing, a word embedding is a representation of a word. The embedding is used in text analysis . Typically, the representation is a real-valued vector that encodes the meaning of the word in such a way that the words that are closer in the vector space are expected to be similar in meaning. [ 1 ]
BigScience Large Open-science Open-access Multilingual Language Model (BLOOM) [1] [2] is a 176-billion-parameter transformer-based autoregressive large language model (LLM). The model, as well as the code base and the data used to train it, are distributed under free licences. [ 3 ]
The Hugging Face Hub is a platform (centralized web service) for hosting: [18]. Git-based code repositories, including discussions and pull requests for projects.; models, also with Git-based version control;
React Native is an open-source UI software framework developed by Meta Platforms (formerly Facebook Inc.). [3] It is used to develop applications for Android, [4]: §Chapter 1 [5] [6] Android TV, [7] iOS, [4]: §Chapter 1 [6] macOS, [8] tvOS, [9] Web, [10] Windows [8] and UWP [11] by enabling developers to use the React framework along with native platform capabilities. [12]
The use of deep learning for knowledge graph embedding has shown good predictive performance even if they are more expensive in the training phase, data-hungry, and often required a pre-trained embedding representation of knowledge graph coming from a different embedding model. [1] [5]
The system uses a deep convolutional neural network to learn a mapping (also called an embedding) from a set of face images to a 128-dimensional Euclidean space, and assesses the similarity between faces based on the square of the Euclidean distance between the images' corresponding normalized vectors in the 128-dimensional Euclidean space.
The Open Group Future Airborne Capability Environment (FACE Consortium) was formed in 2010 to define an open avionics environment for all military airborne platform types. . Today, it is a real-time software-focused professional group made up of industry suppliers, customers, academia, and us