How can I calculate the cosine semantic similarity between pairs of word documents in R? Specifically, I have the plot (i.e., descriptions) of
In the paper describing BERT, there is this paragraph about WordPiece Embeddings. We use WordPiece embeddings (Wu et al., 2016) with a 30,000 token vocab
I would like to store vector features, like Bag-of-Words or Word-Embedding vectors of a large number of texts, in a dataset, stored in a SQL Database. What're t
I am using biobert-embeddings==0.1.2 and torch==1.2.0 versions to embed some documents. But, I get the following error when I try to load the model by from biob
I've problems integrating Bert Embedding Layer in a BiLSTM model for text classification task. My dataset is in the form where each row has 2 columns: text and
This question is a follow-up of tensorflow 2 TextVectorization process tensor and dataset error I would like to make do a word embedding for the processed text
Working in R. I know the pre-trained GloVe embeddings (e.g., "glove.6B.50d.txt") can be found here: https://nlp.stanford.edu/projects/glove/. However, I've had
I want to know the most similar words to another from a pretrained embedding vectors in R. E.g: words similar to "beer". For this, I download the pretrained emb
In LDA model generates different topics everytime i train on the same corpus , by setting the np.random.seed(0), the LDA model will always be initialized and tr