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research.google | ||
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mccormickml.com
[AI summary] The tutorial provides a comprehensive guide to extracting and analyzing BERT embeddings. It begins with tokenization and segment embedding creation, followed by the calculation of word and sentence embeddings using different strategies such as summation and averaging of hidden layers. The context-dependent nature of BERT embeddings is demonstrated by comparing vectors for the word 'bank' in different contexts. The tutorial also discusses pooling strategies, layer choices, and the importance of context in generating meaningful embeddings. It concludes with considerations for special tokens, out-of-vocabulary words, similarity metrics, and implementation options. |
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towardsml.wordpress.com
Unless you have been out of touch with the Deep Learning world, chances are that you have heard about BERT - it has been the talk of the town for the last one year. At the end of 2018 researchers at Google AI Language open-sourced a new technique for Natural Language Processing (NLP) called BERT... |
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ai.googleblog.com
[AI summary] Google Research introduces T5, a unified Text-To-Text Transfer Transformer model and the Colossal Clean Crawled Corpus dataset to achieve state-of-the-art performance across various NLP tasks. |
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gigasquid.github.io
[AI summary] The article demonstrates how to integrate Hugging Face's GPT-2 library into Clojure using the libpython-clj tool to generate text. |
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