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  2. Automatic1111 - Wikipedia

    en.wikipedia.org/wiki/Automatic1111

    AUTOMATIC1111 Stable Diffusion Web UI (SD WebUI, A1111, or Automatic1111 [3]) is an open source generative artificial intelligence program that allows users to generate images from a text prompt. [4] It uses Stable Diffusion as the base model for its image capabilities together with a large set of extensions and features to customize its output.

  3. Stable Diffusion - Wikipedia

    en.wikipedia.org/wiki/Stable_Diffusion

    Stable Diffusion is a deep learning, text-to-image model released in 2022 based on diffusion techniques. The generative artificial intelligence technology is the premier product of Stability AI and is considered to be a part of the ongoing artificial intelligence boom .

  4. Diffusion model - Wikipedia

    en.wikipedia.org/wiki/Diffusion_model

    Stable Diffusion 3 (2024-03) [66] changed the latent diffusion model from the UNet to a Transformer model, and so it is a DiT. It uses rectified flow. It uses rectified flow. Stable Video 4D (2024-07) [ 67 ] is a latent diffusion model for videos of 3D objects.

  5. DreamBooth - Wikipedia

    en.wikipedia.org/wiki/DreamBooth

    Demonstration of the use of DreamBooth to fine-tune the Stable Diffusion v1.5 diffusion model, using training data obtained from Category:Jimmy Wales on Wikimedia Commons. Depicted here are algorithmically generated images of Jimmy Wales, co-founder of Wikipedia, performing bench press exercises at a fitness gym.

  6. Foundation model - Wikipedia

    en.wikipedia.org/wiki/Foundation_model

    The 2022 releases of Stable Diffusion and ChatGPT (initially powered by the GPT-3.5 model) led to foundation models and generative AI entering widespread public discourse. Further, releases of LLaMA , Llama 2, and Mistral in 2023 contributed to a greater emphasis placed on how foundation models are released with open foundation models garnering ...

  7. Training, validation, and test data sets - Wikipedia

    en.wikipedia.org/wiki/Training,_validation,_and...

    A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]

  8. Fine-tuning (deep learning) - Wikipedia

    en.wikipedia.org/wiki/Fine-tuning_(deep_learning)

    In deep learning, fine-tuning is an approach to transfer learning in which the parameters of a pre-trained neural network model are trained on new data. [1] Fine-tuning can be done on the entire neural network, or on only a subset of its layers, in which case the layers that are not being fine-tuned are "frozen" (i.e., not changed during backpropagation). [2]

  9. LAION - Wikipedia

    en.wikipedia.org/wiki/LAION

    LAION (acronym for Large-scale Artificial Intelligence Open Network) is a German non-profit which makes open-sourced artificial intelligence models and datasets. [1] It is best known for releasing a number of large datasets of images and captions scraped from the web which have been used to train a number of high-profile text-to-image models, including Stable Diffusion and Imagen.