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  2. Hugging Face - Wikipedia

    en.wikipedia.org/wiki/Hugging_Face

    The Hugging Face Hub is a platform (centralized web service) for hosting: [19] Git-based code repositories, including discussions and pull requests for projects. models, also with Git-based version control; datasets, mainly in text, images, and audio;

  3. Contrastive Language-Image Pre-training - Wikipedia

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

    Each was trained for 32 epochs. The largest ResNet model took 18 days to train on 592 V100 GPUs. The largest ViT model took 12 days on 256 V100 GPUs. All ViT models were trained on 224x224 image resolution. The ViT-L/14 was then boosted to 336x336 resolution by FixRes, [28] resulting in a model. [note 4] They found this was the best-performing ...

  4. 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.

  5. BLOOM (language model) - Wikipedia

    en.wikipedia.org/wiki/BLOOM_(language_model)

    BigScience Large Open-science Open-access Multilingual Language Model (BLOOM) [1] [2] is a 176-billion-parameter transformer-based autoregressive large language model (LLM). The model, as well as the code base and the data used to train it, are distributed under free licences. [ 3 ]

  6. Text-to-image personalization - Wikipedia

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

    Text-to-Image personalization is a task in deep learning for computer graphics that augments pre-trained text-to-image generative models.In this task, a generative model that was trained on large-scale data (usually a foundation model), is adapted such that it can generate images of novel, user-provided concepts.

  7. GPT-2 - Wikipedia

    en.wikipedia.org/wiki/GPT-2

    While OpenAI did not release the fully-trained model or the corpora it was trained on, description of their methods in prior publications (and the free availability of underlying technology) made it possible for GPT-2 to be replicated by others as free software; one such replication, OpenGPT-2, was released in August 2019, in conjunction with a ...

  8. Ideogram (text-to-image model) - Wikipedia

    en.wikipedia.org/wiki/Ideogram_(text-to-image_model)

    Ideogram was founded in 2022 by Mohammad Norouzi, William Chan, Chitwan Saharia, and Jonathan Ho to develop a better text-to-image model. [3]It was first released with its 0.1 model on August 22, 2023, [4] after receiving $16.5 million in seed funding, which itself was led by Andreessen Horowitz and Index Ventures.

  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.