code: public INDArray inferVector(String text, double learningRate, double minLearningRate, int iterations) {
          if (tokenizerFactory == null)
              throw new IllegalStateException("TokenizerFactory should be defined, prior to predict() call");
  
          if (this.vocab == null || this.vocab.numWords() == 0)
              reassignExistingModel();
  
          List<String> tokens = tokenizerFactory.create(text).getTokens();
          List<VocabWord> document = new ArrayList<>();
          for (String token : tokens) {
              if (vocab.containsWord(token)) {
                  document.add(vocab.wordFor(token));
              }
          }
  
          if (document.isEmpty())
              throw new ND4JIllegalStateException("Text passed for inference has no matches in model vocabulary.");
  
          return inferVector(document, learningRate, minLearningRate, iterations);
      }
docs: This method calculates inferred vector for given text
  
  @param text
  @return