code: private SequenceLabelerModel loadModel(final String lang,
        final String modelName, final Boolean useModelCache) {
      final long lStartTime = new Date().getTime();
      try {
        if (useModelCache) {
          synchronized (seqModels) {
            if (!seqModels.containsKey(lang + modelName)) {
              SequenceLabelerModel model = new SequenceLabelerModel(new FileInputStream(modelName));
              seqModels.put(lang + modelName, model);
            }
          }
        } else {
          synchronized (seqModels) {
            if (!seqModels.containsKey(lang + modelName)) {
              SequenceLabelerModel model = new SequenceLabelerModel(new FileInputStream(modelName));
              seqModels.put(lang + modelName, model);
            }
          }
        }
      } catch (final IOException e) {
        e.printStackTrace();
      }
      final long lEndTime = new Date().getTime();
      final long difference = lEndTime - lStartTime;
      System.err.println("IXA pipes Sequence model loaded in: " + difference
          + " miliseconds ... [DONE]");
      return seqModels.get(lang + modelName);
    }
docs: Loads statically the probabilistic model. Every instance of this finder
  will share the same model.
  
  @param lang
  the language
  @param model
  the model to be loaded
  @return the model as a {@link SequenceLabelerModel} object