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The Transformers library is a Python package that contains open-source implementations of transformer models for text, image, and audio tasks. It is compatible with the PyTorch, TensorFlow and JAX deep learning libraries and includes implementations of notable models like BERT and GPT-2. [16]
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.
The Pile is an 886.03 GB diverse, open-source dataset of English text created as a training dataset for large language models (LLMs). It was constructed by EleutherAI in 2020 and publicly released on December 31 of that year.
Diagram of the latent diffusion architecture used by Stable Diffusion The denoising process used by 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 ...
An improved flagship model, Flux 1.1 Pro was released on 2 October 2024. [25] [26] Two additional modes were added on 6 November, Ultra which can generate image at four times higher resolution and up to 4 megapixel without affecting generation speed and Raw which can generate hyper-realistic image in the style of candid photography. [27] [28] [29]
20 photos of leaves for each of 32 species. None. 637 Images, text Classification, clustering 2015 [313] [314] T. Munisami et al. Oxford Flower Dataset 17 category dataset of flowers. Train/test splits, labeled images, 1360 Images, text Classification 2006 [315] [316] M-E Nilsback et al. Plant Seedlings Dataset 12 category dataset of plant ...
Food & Wine / Getty Images. For food and beverage journalists, each December is a buffet of piquant triumph and bitter humiliation as we assess our food trend predictions from the previous year ...
Open-source artificial intelligence is an AI system that is freely available to use, study, modify, and share. [1] These attributes extend to each of the system's components, including datasets, code, and model parameters, promoting a collaborative and transparent approach to AI development. [1]