Data Science, Machine Learning, NLP, Transformers, Word Embeddings.
+ " [SEP]" tokenized_texts.append(tokenizer.tokenize(marked_text)) # Add the encoded sentence to the list. input_ids.append(encoded_dict['input_ids']) # Convert the list into tensor. input_ids = torch.cat(input_ids, dim=0) Segment ID. BERT is trained on and expects sentence pairs using 1s and 0s to