4 нояб. 2019 г. · Using the transformers library is the easiest way I know of to get sentence embeddings from BERT. There are, however, many ways to measure similarity between ...

13 апр. 2021 г. · How to just extract embeddings from BERT using some dictionary of words and use word representations for futher work? Can we solve inside BERT ...

28 дек. 2020 г. · I'm trying to get word embeddings for clinical data using microsoft/pubmedbert. I have 3.6 million text rows. Converting texts to vectors for 10k rows takes ...

19 янв. 2022 г. · One approach to derive sentence embeddings by mean pooling excluding padding tokens can be taken from Sentence Transformers.

3 мая 2021 г. · I am trying to figure how the embedding layer works for the pretrained BERT-base model. I am using pytorch and trying to dissect the following model.

17 нояб. 2020 г. · BERT provides word-level embeddings, not sentence embedding. You are correct about averaging word embedding to get the sentence embedding part.

12 янв. 2024 г. · This was studied in the original BERT article, which concluded that the best approach was to concatenate the states of the last 4 layers.

3 мая 2023 г. · How can I generate embeddings using previously generated BERT embeddings and feed them to an RNN? Ask Question. Asked 1 year, 6 months ago.

14 янв. 2022 г. · It seems to add up the subword embeddings of each word (only the last BERT layer) and concatenate each resulting vector into a tensor for the whole sentence.

1 мар. 2024 г. · I have a BERT model which I want to use for sentiment analysis/classification. Eg I have some tweets that need to get a POSITIVE,NEGATIVE or NEUTRAL label.