frankfliu

# serving.properties can be used to define model's metadata, all the arguments will be
# passed to TranslatorFactory to create proper Translator

# defines model's application
application=nlp/question_answer

# defines the model's engine, can be overrid by Criteria.optEngine()
engine=PyTorch

# defines TranslatorFactory, can be overrid by Criteria.optTranslator() or Criteria.optTranslatorFactory()

frankfliu

import ai.djl.Application;
import ai.djl.ModelException;
import ai.djl.inference.Predictor;
import ai.djl.modality.Classifications;
import ai.djl.modality.cv.Image;
import ai.djl.modality.cv.ImageFactory;
import ai.djl.repository.zoo.Criteria;
import ai.djl.repository.zoo.ZooModel;
import ai.djl.translate.TranslateException;

frankfliu

import ai.djl.Application;
import ai.djl.ModelException;
import ai.djl.inference.Predictor;
import ai.djl.modality.Classifications;
import ai.djl.modality.cv.Image;
import ai.djl.modality.cv.ImageFactory;
import ai.djl.repository.zoo.Criteria;
import ai.djl.repository.zoo.ZooModel;
import ai.djl.translate.TranslateException;

frankfliu

import ai.djl.Application;
import ai.djl.ModelException;
import ai.djl.inference.Predictor;
import ai.djl.modality.Classifications;
import ai.djl.modality.cv.Image;
import ai.djl.modality.cv.ImageFactory;
import ai.djl.repository.zoo.Criteria;
import ai.djl.repository.zoo.ZooModel;
import ai.djl.translate.TranslateException;

frankfliu

import ai.djl.Application;
import ai.djl.ModelException;
import ai.djl.inference.Predictor;
import ai.djl.modality.Classifications;
import ai.djl.modality.cv.Image;
import ai.djl.modality.cv.ImageFactory;
import ai.djl.repository.zoo.Criteria;
import ai.djl.repository.zoo.ZooModel;
import ai.djl.translate.TranslateException;

frankfliu

package ai.djl.examples;

import ai.djl.inference.Predictor;
import ai.djl.modality.Classifications;
import ai.djl.modality.cv.*;
import ai.djl.modality.cv.transform.*;
import ai.djl.modality.cv.translator.*;
import ai.djl.repository.zoo.*;

public class Example {