How to use opennlp.tools.ml.model

public AbstractModel(Context[] params, String[] predLabels, String[] outcomeNames) {
 init(predLabels, params, outcomeNames);
 this.evalParams = new EvalParameters(params, outcomeNames.length);
}

/**
 * Retrieves an array of all possible part-of-speech tags from the
 * tagger.
 *
 * @return String[]
 */
public String[] getAllPosTags() {
 return model.getOutcomes();
}

 @Override
 public void writeUTF(String s) throws IOException {
  delegateWriter.writeUTF(s);
 }
}

private Event createEvent(String obs) {
 int lastSpace = obs.lastIndexOf(' ');
 if (lastSpace == -1)
  return null;
 else {
  String[] contexts = obs.substring(0,lastSpace).split("\\s+");
  float[] values = RealValueFileEventStream.parseContexts(contexts);
  return new Event(obs.substring(lastSpace + 1),contexts,values);
 }
}

 @Override
 public String[] getOutcomes() {
  String[] outcomes = new String[model.getNumOutcomes()];

  for (int i = 0; i < model.getNumOutcomes(); i++) {
   outcomes[i] = model.getOutcome(i);
  }

  return outcomes;
 }
}

public AbstractModel create(InputStream in) throws IOException {
 return new GenericModelReader(new BinaryFileDataReader(in)).getModel();
}

protected double[] initOutcomeTotals(String[] outcomeNames, Context[] params) {
 double[] outcomeTotals = new double[outcomeNames.length];
 for (int i = 0; i < params.length; ++i) {
  Context context = params[i];
  for (int j = 0; j < context.getOutcomes().length; ++j) {
   int outcome = context.getOutcomes()[j];
   double count = context.getParameters()[j];
   outcomeTotals[outcome] += count;
  }
 }
 return outcomeTotals;
}

protected String[] getPredicates() throws java.io.IOException {
 NUM_PREDS = readInt();
 String[] predLabels = new String[NUM_PREDS];
 for (int i = 0; i < NUM_PREDS; i++)
   predLabels[i] = readUTF();
 return predLabels;
}

 public Sequence[] topKLemmaClasses(String[] sentence, String[] tags, double minSequenceScore) {
  return model.bestSequences(DEFAULT_BEAM_SIZE, sentence, new Object[] { tags }, minSequenceScore,
    contextGenerator, sequenceValidator);
 }
}

/**
 * Constructor which directly instantiates the DataInputStream containing
 * the model contents.
 *
 * @param dis The DataInputStream containing the model information.
 */
public BinaryNaiveBayesModelReader(DataInputStream dis) {
 super(new BinaryFileDataReader(dis));
}

/**
 * Constructor which directly instantiates the BufferedReader containing
 * the model contents.
 *
 * @param br The BufferedReader containing the model information.
 */
public PlainTextNaiveBayesModelReader(BufferedReader br) {
 super(new PlainTextFileDataReader(br));
}

/**
 * Implement as needed for the format the model is stored in.
 */
public double readDouble() throws java.io.IOException {
 return dataReader.readDouble();
}

protected AbstractModel(Context[] params, String[] predLabels,
  Map<String, Context> pmap, String[] outcomeNames) {
 this.pmap = pmap;
 this.outcomeNames =  outcomeNames;
 this.evalParams = new EvalParameters(params,outcomeNames.length);
}

/**
 * Implement as needed for the format the model is stored in.
 */
public String readUTF() throws java.io.IOException {
 return dataReader.readUTF();
}

@Override
public void writeDouble(double d) throws IOException {
 delegateWriter.writeDouble(d);
}

@Override
public void persist() throws IOException {
 delegateWriter.persist();
}

/**
 * Implement as needed for the format the model is stored in.
 */
public int readInt() throws java.io.IOException {
 return dataReader.readInt();
}

protected String[] getOutcomes() throws java.io.IOException {
 int numOutcomes = readInt();
 String[] outcomeLabels = new String[numOutcomes];
 for (int i = 0; i < numOutcomes; i++) outcomeLabels[i] = readUTF();
 return outcomeLabels;
}

 /**
  * Constructor which directly instantiates the DataInputStream containing the
  * model contents.
  *
  * @param dis
  *          The DataInputStream containing the model information.
  */
 public BinaryGISModelReader(DataInputStream dis) {
  super(new BinaryFileDataReader(dis));
 }
}

 /**
  * Constructor which directly instantiates the DataInputStream containing the
  * model contents.
  *
  * @param dis
  *          The DataInputStream containing the model information.
  */
 public BinaryQNModelReader(DataInputStream dis) {
  super(new BinaryFileDataReader(dis));
 }
}