Charformer Fast Character Transformers via Gradient-based Subword Tokenization Tokenizer explained

What is tokenization Ms Coffee Bean explains tokenization in general explains why flexible tokenization is important and then moves onto explaining the Charformer Fast Character Transformers via Gradient-based Subword Tokenization paper explained and visualized Paper Tay Yi Vinh Tran Sebastian Ruder Jai Gupta Hyung Won Chung Dara Bahri Zhen Qin Simon Baumgartner Cong Yu and Donald Metzler Charformer Fast Character Transformers via Gradient-based Subword Tokenization 2021 a https 3A 2F 2Farxiv org 2Fabs 2F2106 12672 a Replacing self-attention with the Fourier Transform a https 3A 2F 2Fyoutu be 2Fj7pWPdGEfMA a Convolutions instead of self-attention When is a Transformer not a Transformer anymore a https 3A 2F 2Fyoutu be 2FxchDU2VMR4M a Transformer explained a https 3A 2F 2Fyoutu be 2FFWFA4DGuzSc a Outline 00 00 What are tokenizers good for 02 49 Where does rigid tokenization fail 03 51 Charformer end-to-end tokenization 08 33 Again but in summary 09 57 Reducing the sequence length 10 37 Meta-comments on token mixing Optionally pay us a coffee to help with our Coffee Bean production Patreon a https 3A 2F 2Fwww patreon com 2FAICoffeeBreak a Ko-fi a https 3A 2F 2Fko-fi com 2Faicoffeebreak a Links YouTube a https 3A 2F 2Fwww youtube com 2FAICoffeeBreak a Twitter a https 3A 2F 2Ftwitter com 2FAICoffeeBreak a Reddit a https 3A 2F 2Fwww reddit com 2Fr 2FAICoffeeBreak 2F a AICoffeeBreak MsCoffeeBean MachineLearning AI research

• Select a category

  1