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  2. Help:WordToWiki - Wikipedia

    en.wikipedia.org/wiki/Help:WordToWiki

    Open your document in Word, and "save as" an HTML file. Open the HTML file in a text editor and copy the HTML source code to the clipboard. Paste the HTML source into the large text box labeled "HTML markup:" on the html to wiki page. Click the blue Convert button at the bottom of the page.

  3. Wikipedia:Tools/Editing tools - Wikipedia

    en.wikipedia.org/wiki/Wikipedia:Tools/Editing_tools

    Microsoft Office Word Add-in For MediaWiki: Converts Word documents to wiki formatting. Doesn't do images. This may not work on newer versions of Word. Excel2Wiki tool for converting Excel tables to wiki tables. Transferring a single wiki page in MediaWiki to Word is easy, just save the desired webpage and then open the page in Microsoft Word.

  4. Text-to-image model - Wikipedia

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

    An image conditioned on the prompt an astronaut riding a horse, by Hiroshige, generated by Stable Diffusion 3.5, a large-scale text-to-image model first released in 2022. A text-to-image model is a machine learning model which takes an input natural language description and produces an image matching that description.

  5. Text-to-image personalization - Wikipedia

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

    Text-to-Image personalization is a task in deep learning for computer graphics that augments pre-trained text-to-image generative models. In this task, a generative model that was trained on large-scale data (usually a foundation model ), is adapted such that it can generate images of novel, user-provided concepts.

  6. ImageMagick - Wikipedia

    en.wikipedia.org/wiki/ImageMagick

    The software mainly consists of a number of command-line interface utilities for manipulating images. ImageMagick does not have a robust graphical user interface to edit images as do Adobe Photoshop and GIMP, but does include – for Unix-like operating systems – a basic native X Window GUI (called IMDisplay) for rendering and manipulating images and API libraries for many programming languages.

  7. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    The idea of skip-gram is that the vector of a word should be close to the vector of each of its neighbors. The idea of CBOW is that the vector-sum of a word's neighbors should be close to the vector of the word. In the original publication, "closeness" is measured by softmax, but the framework allows other ways to measure closeness.