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The total number of words in this dataset is similar in scale to the WebText dataset used for training GPT-2, which contains about 40 gigabytes of text data. [ 1 ] The dataset contains 500,000 text-queries, with up to 20,000 (image, text) pairs per query.
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.
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Positive examples are those that match the target. For example, if training a classifier to identify birds, the positive training data would include images that contain birds. Negative examples would be images that do not. [9] Contrastive self-supervised learning uses both positive and negative examples.
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.
VIN on a Chinese moped VIN on a 1996 Porsche 993 GT2 VIN visible in the windshield VIN recorded on a Chinese vehicle licence. A vehicle identification number (VIN; also called a chassis number or frame number) is a unique code, including a serial number, used by the automotive industry to identify individual motor vehicles, towed vehicles, motorcycles, scooters and mopeds, as defined by the ...
Restricted Boltzmann train one layer at a time and approximate equilibrium state with a 3-segment pass, not performing back propagation. Restricted Boltzmann uses both supervised and unsupervised on different RBM for pre-training for classification and recognition. The training uses contrastive divergence with Gibbs sampling: Δw ij = e*(p ij ...
In the study of images within computer science, the abstract data type "image" (or potentially several such types) is a central focus, along with its various implementations. [2] Three main groups of algorithms are relevant to this data type in computational visualistics: