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  2. Contrastive Language-Image Pre-training - Wikipedia

    en.wikipedia.org/wiki/Contrastive_Language-Image...

    The CLIP method trains a pair of models contrastively. [1] One model takes in a piece of text as input and outputs a single vector representing its semantic content. The other model takes in an image and similarly outputs a single vector representing its visual content.

  3. Stable Diffusion - Wikipedia

    en.wikipedia.org/wiki/Stable_Diffusion

    The model generates images by iteratively denoising random noise until a configured number of steps have been reached, guided by the CLIP text encoder pretrained on concepts along with the attention mechanism, resulting in the desired image depicting a representation of the trained concept.

  4. Foundation model - Wikipedia

    en.wikipedia.org/wiki/Foundation_model

    A foundation model, also known as large X model (LxM), is a machine learning or deep learning model that is trained on vast datasets so it can be applied across a wide range of use cases. [1] Generative AI applications like Large Language Models are often examples of foundation models.

  5. DALL-E - Wikipedia

    en.wikipedia.org/wiki/DALL-E

    DALL-E was developed and announced to the public in conjunction with CLIP (Contrastive Language-Image Pre-training). [23] CLIP is a separate model based on contrastive learning that was trained on 400 million pairs of images with text captions scraped from the Internet. Its role is to "understand and rank" DALL-E's output by predicting which ...

  6. Multimodal learning - Wikipedia

    en.wikipedia.org/wiki/Multimodal_learning

    Multimodal learning is a type of deep learning that integrates and processes multiple types of data, referred to as modalities, such as text, audio, images, or video.This integration allows for a more holistic understanding of complex data, improving model performance in tasks like visual question answering, cross-modal retrieval, [1] text-to-image generation, [2] aesthetic ranking, [3] and ...

  7. Generative pre-trained transformer - Wikipedia

    en.wikipedia.org/wiki/Generative_pre-trained...

    Generative pretraining (GP) was a long-established concept in machine learning applications. [16] [17] It was originally used as a form of semi-supervised learning, as the model is trained first on an unlabelled dataset (pretraining step) by learning to generate datapoints in the dataset, and then it is trained to classify a labelled dataset.

  8. Teddi Mellencamp Reshares Graphic Image of Surgery Scar ... - AOL

    www.aol.com/teddi-mellencamp-reshares-graphic...

    Teddi Mellencamp is using her own health journey to create awareness for World Cancer Day.. On Tuesday, Feb. 4, the Real Housewives of Beverly Hills alum, 43, re-posted a graphic photo of her ...

  9. Text-to-image model - Wikipedia

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

    A common algorithmic metric for assessing image quality and diversity is the Inception Score (IS), which is based on the distribution of labels predicted by a pretrained Inceptionv3 image classification model when applied to a sample of images generated by the text-to-image model. The score is increased when the image classification model ...