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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]
The Pile was originally developed to train EleutherAI's GPT-Neo models [8] [9] [10] but has become widely used to train other models, including Microsoft's Megatron-Turing Natural Language Generation, [11] [12] Meta AI's Open Pre-trained Transformers, [13] LLaMA, [14] and Galactica, [15] Stanford University's BioMedLM 2.7B, [16] the Beijing ...
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 seedlings. Labelled images, segmented images, 5544 Images Classification, detection 2017 [317] Giselsson et al. Fruits-360 Database with images of 131 fruits and vegetables.
A foundation model, also known as large X model (LxM), is a machine learning or deep learning model that is trained on vast datasets so it can be applied across a wide range of use cases. [1] Generative AI applications like Large Language Models are often examples of foundation models.
Nearly 200,000 books written by a wide range of authors, including Nora Roberts, are being used to train artificial intelligence systems, according to a recent report. No one asked for the writers ...
One such recent development is the use of sophisticated artificial intelligence ("AI") technologies capable of producing expressive material. These technologies "train" on vast quantities of preexisting human-authored works and use inferences from that training to generate new content.
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]
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 ]