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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. Image conversion - Wikipedia

    en.wikipedia.org/wiki/Image_conversion

    Like any resampling operation, changing image size and bit depth are lossy in all cases of downsampling, such as 30-bit to 24-bit or 24-bit to 8-bit palette-based images.. While increasing bit depth is usually lossless, increasing image size can introduce aliasing or other undesired artifa

  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. WordPerfect - Wikipedia

    en.wikipedia.org/wiki/WordPerfect

    WordPerfect (WP) is a word processing application, now owned by Alludo, [3] with a long history on multiple personal computer platforms. At the height of its popularity in the 1980s and early 1990s, it was the market leader of word processors, displacing the prior market leader WordStar.

  6. Freemake Video Converter - Wikipedia

    en.wikipedia.org/wiki/Freemake_Video_Converter

    Freemake Video Converter 2.0 was a major update that integrated two new functions: ripping video from online portals and Blu-ray disc creation and burning. [13] [14] Version 2.1 implemented suggestions from users, including support for subtitles, ISO image creation, and DVD to DVD/Blu-ray conversion. [15]

  7. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    Word2vec is a group of related models that are used to produce word embeddings.These models are shallow, two-layer neural networks that are trained to reconstruct linguistic contexts of words.