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BERT (language model) - Wikipedia
Bidirectional encoder representations from transf ormers (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 transf ormer architecture. It is notable for its dramatic improvement over previous state-of-the-art models, and as an early example of a large langu
Itisango 2021/11/13
â€œBERT is a transformer-based machine learning technique for natural language processing (NLP) pre-training developed by Google. BERT was created and published in 2018 by Jacob Devlin and his colleagues from Google. In 2019, Google announced that it had begun leveraging BERTâ€

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Kaggle: The Home of Data Science
Kaggle is the worldâ€™s largest data science community with powerful tools and resources to help you achieve your data science goals.
Itisango 2021/11/13
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!pip install --upgrade tensorflow_hub import tensorflow_hub as hub model = hub.KerasLayer("https://tfhub.dev/google/nnlm-en-dim128/2") embeddings = model(["The rain in Spain.", "falls", "mainly", "In the plain!"]) print(embeddings.shape) #(4,128)
Itisango 2021/11/13
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Itisango 2021/08/15
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Itisango 2018/03/01
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Itisango 2017/05/02
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Itisango 2015/07/09
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ãƒ¡ãƒ¼ãƒªãƒ³ã‚°ãƒªã‚¹ãƒˆ - MergeDoc - OSDN
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Itisango 2015/06/25
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Itisango 2015/06/16
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Itisango 2015/04/12
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The Pkg-anthy-devel Archives
Itisango 2015/01/31
They #discuss about #Egg #Tamago and #Anthy in #Debian #Alioth

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Itisango 2015/01/31
They #discuss about #Egg #Tamago and #Anthy in #Debian #Alioth

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