fastBERTtokens: Tokenizing for BERT in parallel

Versione 1.0.0 (1,43 KB) da Ralf Elsas
This function simply divides your text into batches, and tokenizes in parallel. Provides significant speed-up.
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Aggiornato 24 feb 2023

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Function to use Matlab BERT tokenizer in parallel
This function simply divides your text into batches, and tokenizes in parallel. As the Matlab tokenizer is very slow when run on a single processor for large data, this provides a significant speed-up. On an i7-10875H laptop with 8 logical units, tokenizing 76k sentences takes about 100 seconds.
Also note that providing the Matlab BERT model is important, as different BERT models use different encodings for the special BERT tokens like [SEP] etc.

Cita come

Ralf Elsas (2024). fastBERTtokens: Tokenizing for BERT in parallel (https://www.mathworks.com/matlabcentral/fileexchange/125295-fastberttokens-tokenizing-for-bert-in-parallel), MATLAB Central File Exchange. Recuperato .

Compatibilità della release di MATLAB
Creato con R2022b
Compatibile con R2021a e release successive
Compatibilità della piattaforma
Windows macOS Linux
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Ispirato da: Transformer Models

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Versione Pubblicato Note della release
1.0.0