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  2. Attention Is All You Need - Wikipedia

    en.wikipedia.org/wiki/Attention_Is_All_You_Need

    Attention Is All You Need. An illustration of main components of the transformer model from the paper. " Attention Is All You Need " [1] is a 2017 landmark [2][3] research paper in machine learning authored by eight scientists working at Google. The paper introduced a new deep learning architecture known as the transformer, based on the ...

  3. Transformer (deep learning architecture) - Wikipedia

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

    A transformer is a deep learning architecture developed by researchers at Google and based on the multi-head attention mechanism, proposed in the 2017 paper "Attention Is All You Need". [1] Text is converted to numerical representations called tokens, and each token is converted into a vector via lookup from a word embedding table. [1]

  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. T5 models are usually pretrained on a massive ...

  5. Solid Converter PDF - Wikipedia

    en.wikipedia.org/wiki/Solid_Converter_PDF

    Solid Converter PDF. Solid Converter PDF is document reconstruction software from Solid Documents which converts PDF files to editable formats. Originally released for the Microsoft Windows operating system, a Mac OS X version was released in 2010. The current versions are Solid Converter PDF 9.0 for Windows and Solid PDF to Word for Mac 2.1.

  6. BERT (language model) - Wikipedia

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

    BERT (language model) Bidirectional encoder representations from transformers (BERT) is a language model introduced in October 2018 by researchers at Google. [1][2] It learns to represent text as a sequence of vectors using self-supervised learning. It uses the encoder-only transformer architecture.

  7. How much prize money do the New York City marathon ... - AOL

    www.aol.com/much-prize-money-york-city-100022994...

    The prize money for top finishers: 3rd place: $40,0004th place: $25,0005th place: $15,0006th place: $10,0007th place: $7,5008th place: $5,0009th place: $2,50010th place: $2,000. Additional rewards ...

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