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  2. ComfyUI - Wikipedia

    en.wikipedia.org/wiki/ComfyUI

    ComfyUI is an open source, node-based program that allows users to generate images from a series of text prompts.It uses free diffusion models such as Stable Diffusion as the base model for its image capabilities combined with other tools such as ControlNet and LCM Low-rank adaptation with each tool being represented by a node in the program.

  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. 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.

  5. DreamBooth - Wikipedia

    en.wikipedia.org/wiki/DreamBooth

    DreamBooth can be used to fine-tune models such as Stable Diffusion, where it may alleviate a common shortcoming of Stable Diffusion not being able to adequately generate images of specific individual people. [4] Such a use case is quite VRAM intensive, however, and thus cost-prohibitive for hobbyist users. [4]

  6. Diffusion model - Wikipedia

    en.wikipedia.org/wiki/Diffusion_model

    The goal of diffusion models is to learn a diffusion process for a given dataset, such that the process can generate new elements that are distributed similarly as the original dataset. A diffusion model models data as generated by a diffusion process, whereby a new datum performs a random walk with drift through the space of all possible data. [2]

  7. Latent diffusion model - Wikipedia

    en.wikipedia.org/wiki/Latent_Diffusion_Model

    The Latent Diffusion Model (LDM) [1] is a diffusion model architecture developed by the CompVis (Computer Vision & Learning) [2] group at LMU Munich. [ 3 ] Introduced in 2015, diffusion models (DMs) are trained with the objective of removing successive applications of noise (commonly Gaussian ) on training images.

  8. List of emerging technologies - Wikipedia

    en.wikipedia.org/wiki/List_of_emerging_technologies

    Research and development, diffusion Neuromorphic engineering: Research and development Optical computing: Hypothetical, experiments; some components of integrated circuits have been developed [36] Smaller, faster, lower power consuming computing Quantum computing: Experiments, [37] commercialization, [38] early diffusion

  9. Mixture of experts - Wikipedia

    en.wikipedia.org/wiki/Mixture_of_experts

    Other than language models, Vision MoE [36] is a Transformer model with MoE layers. They demonstrated it by training a model with 15 billion parameters. MoE Transformer has also been applied for diffusion models. [37] A series of large language models from Google used MoE. GShard [38] uses MoE with up to top-2 experts per layer. Specifically ...

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