Data Science, Machine Learning, NLP, Transformers, Word Embeddings.
attention_masks = [] tokenized_texts = [] for sent in sentences: encoded_dict = tokenizer.encode_plus( sent, add_special_tokens = True, truncation=True, max_length = 48, pad_to_max_length = True, return_tensors = 'pt', ) # Save tokens from sentence as a separate array. marked_text = "[CLS] " + sent