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  2. Transformer (deep learning architecture) - Wikipedia

    en.wikipedia.org/wiki/Transformer_(deep_learning...

    Transformer architecture is now used in many generative models that contribute to the ongoing AI boom. In language modelling, ELMo (2018) was a bi-directional LSTM that produces contextualized word embeddings, improving upon the line of research from bag of words and word2vec. It was followed by BERT (2018), an encoder-only Transformer model. [35]

  3. Generative pre-trained transformer - Wikipedia

    en.wikipedia.org/wiki/Generative_pre-trained...

    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.

  4. T5 (language model) - Wikipedia

    en.wikipedia.org/wiki/T5_(language_model)

    T5 (Text-to-Text Transfer Transformer) is a series of large language models developed by Google AI introduced in 2019. [ 1 ] [ 2 ] Like the original Transformer model, [ 3 ] T5 models are encoder-decoder Transformers , where the encoder processes the input text, and the decoder generates the output text.

  5. Transformer (deep learning architecture) - Wikipedia

    en.wikipedia.org/api/rest_v1/page/pdf/...

    A standard Transformer architecture, showing on the left an encoder, and on the right a decoder. Note: it uses the pre-LN convention, which is different from the post-LN convention used in the original 2017 Transformer. Transformer (deep learning architecture) A transformer is a deep learning architecture that was developed

  6. Attention Is All You Need - Wikipedia

    en.wikipedia.org/wiki/Attention_Is_All_You_Need

    Transformer architecture is now used in many generative models that contribute to the ongoing AI boom. In language modelling, ELMo (2018) was a bi-directional LSTM that produces contextualized word embeddings, improving upon the line of research from bag of words and word2vec. It was followed by BERT (2018), an encoder-only Transformer model. [33]

  7. GPT-3 - Wikipedia

    en.wikipedia.org/wiki/GPT-3

    Generative Pre-trained Transformer 3 (GPT-3) is a large language model released by OpenAI in 2020. Like its predecessor, GPT-2 , it is a decoder-only [ 2 ] transformer model of deep neural network, which supersedes recurrence and convolution-based architectures with a technique known as " attention ". [ 3 ]

  8. GPT-1 - Wikipedia

    en.wikipedia.org/wiki/GPT-1

    Generative Pre-trained Transformer 1 (GPT-1) was the first of OpenAI's large language models following Google's invention of the transformer architecture in 2017. [2] In June 2018, OpenAI released a paper entitled "Improving Language Understanding by Generative Pre-Training", [ 3 ] in which they introduced that initial model along with the ...

  9. Vision transformer - Wikipedia

    en.wikipedia.org/wiki/Vision_transformer

    A vision transformer (ViT) is a transformer designed for computer vision. [1] A ViT decomposes an input image into a series of patches (rather than text into tokens ), serializes each patch into a vector, and maps it to a smaller dimension with a single matrix multiplication .

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