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  2. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    e. Word2vec is a technique in natural language processing (NLP) for obtaining vector representations of words. These vectors capture information about the meaning of the word based on the surrounding words. The word2vec algorithm estimates these representations by modeling text in a large corpus. Once trained, such a model can detect synonymous ...

  3. Vector graphics - Wikipedia

    en.wikipedia.org/wiki/Vector_graphics

    Vector graphics. Vector graphics are a form of computer graphics in which visual images are created directly from geometric shapes defined on a Cartesian plane, such as points, lines, curves and polygons. The associated mechanisms may include vector display and printing hardware, vector data models and file formats, as well as the software ...

  4. Text-to-image model - Wikipedia

    en.wikipedia.org/wiki/Text-to-image_model

    A text-to-image model is a machine learning model which takes an input natural language description and produces an image matching that description. Text-to-image models began to be developed in the mid-2010s during the beginnings of the AI boom, as a result of advances in deep neural networks. In 2022, the output of state-of-the-art text-to ...

  5. Help:WordToWiki - Wikipedia

    en.wikipedia.org/wiki/Help:WordToWiki

    OpenOffice or LibreOffice. LibreOffice Writer can save Word documents directly to wikitext: go to File → Export → Save as type: Mediawiki. (For Linux users it may be necessary to install the library libreoffice-wiki-publisher ). Alternatively, use the command-line utility like this: soffice--headless--convert-totxt:MediaWikimydocument.doc.

  6. Word embedding - Wikipedia

    en.wikipedia.org/wiki/Word_embedding

    t. e. In natural language processing(NLP), a word embeddingis a representation of a word. The embedding is used in text analysis. Typically, the representation is a real-valuedvector 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] Word embeddings can ...

  7. Transformer (deep learning architecture) - Wikipedia

    en.wikipedia.org/wiki/Transformer_(deep_learning...

    Instead, it uses a decoder-only Transformer that autoregressively generates a text, followed by the token representation of an image, which is then converted by a variational autoencoder to an image. [91] Parti is an encoder-decoder Transformer, where the encoder processes a text prompt, and the decoder generates a token representation of an image.

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