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2. 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.

3. Transformer (deep learning architecture) - Wikipedia

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

   t. e. 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. A transformer is a deep learning architecture developed by researchers at Google and based on the multi-head attention ...

4. Attention Is All You Need - Wikipedia

   en.wikipedia.org/wiki/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 attention mechanism proposed in ...

5. Transformer (Lou Reed album) - Wikipedia

   en.wikipedia.org/wiki/Transformer_(Lou_Reed_album)

   Released: April 1973. Transformer is the second solo studio album by American recording artist Lou Reed. Produced by David Bowie and Mick Ronson, the album was released on November 8, 1972 by RCA Records. It is considered an influential landmark of the glam rock genre, anchored by Reed's most successful single, "Walk on the Wild Side", which ...

6. BERT (language model) - Wikipedia

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

   Apache 2.0. Website. arxiv .org /abs /1810 .04805. Bidirectional Encoder Representations from Transformers ( BERT) is a language model introduced in October 2018 by researchers at Google. [ 1][ 2] It learned by self-supervised learning to represent text as a sequence of vectors. It had the transformer encoder architecture.

7. 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] [18] 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.