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  2. 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.

  3. Adobe Firefly - Wikipedia

    en.wikipedia.org/wiki/Adobe_Firefly

    Adobe Firefly is a generative machine learning text-to-image model included as part of Adobe Creative Cloud.It is currently being tested in an open beta phase. [1] [2] [3]Adobe Firefly is developed using Adobe's Sensei platform.

  4. Picasa - Wikipedia

    en.wikipedia.org/wiki/Picasa

    Other simple editing features include adding text to the image. Picasa supports Google's WebP image format as well as the JPG format and most Raw image format (RAW files). A user can view and edit RAW files and save the finished edit (as JPG, or other forms) without any changes to the original RAW file.

  5. Media Transfer Protocol - Wikipedia

    en.wikipedia.org/wiki/Media_Transfer_Protocol

    MTP is a high level file transfer protocol, as opposed to a general storage protocol like USB mass storage.That means that the MTP client (computer) does not see an array of byte blocks that makes up a data structure that makes up a file system, but instead speaks in terms of files and folders to the MTP device.

  6. Transformers: Rescue Bots Academy - Wikipedia

    en.wikipedia.org/wiki/Transformers:_Rescue_Bots...

    Transformers: Rescue Bots Academy (or simply Rescue Bots Academy) is an animated children's television series on Discovery Family.Based on toy manufacturer Hasbro's Transformers franchise, the series is a sequel of Transformers: Rescue Bots, sharing the name with the Rescue Bots season three episode called "Rescue Bots Academy".

  7. LaMDA - Wikipedia

    en.wikipedia.org/wiki/LaMDA

    LaMDA is a decoder-only Transformer language model. [48] It is pre-trained on a text corpus that includes both documents and dialogs consisting of 1.56 trillion words, [ 49 ] and is then trained with fine-tuning data generated by manually annotated responses for "sensibleness, interestingness, and safety".

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