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fastText is a library for learning of word embeddings and text classification created by Facebook ... Facebook makes available pretrained models for 294 languages. ...
Use of OLE objects limits interoperability, because these objects are not widely supported in programs for viewing or editing files outside of Microsoft Windows (e.g., embedding of other files inside the file, such as tables or charts from a spreadsheet application in a text document or presentation file).
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]
AppleWorks (formerly ClarisWorks presentation editing) - Classic Mac OS, Mac OS X, Windows 2000 or later; CA-Cricket Presents - Apple Macintosh, Windows; Gobe Productive - BeOS, Linux, Windows; Harvard Graphics - DOS, Windows; IBM Lotus Symphony - Linux, Mac OS X, Windows; Lotus Freelance Graphics - Windows; Jarte - Windows; MagicPoint - Unix ...
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.
LibreOffice Impress, one of the most popular free and open-source presentation programs. In computing, a presentation program (also called presentation software) is a software package used to display information in the form of a slide show. It has three major functions: [1] an editor that allows text to be inserted and formatted
The Web Embedding Fonts Tool, or WEFT, is Microsoft's utility for generating embeddable web fonts.. WEFT is used by webmasters to create 'font objects' that are linked to their web pages so that users using Microsoft's Internet Explorer web browser will see the pages displayed in the font style contained within the font object.
Unlike previous models, BERT is a deeply bidirectional, unsupervised language representation, pre-trained using only a plain text corpus. Context-free models such as word2vec or GloVe generate a single word embedding representation for each word in the vocabulary, whereas BERT takes into account the context for each occurrence of a given word ...
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