# Java

- [TensorFlow (2.x)](https://serving.konduit.ai/0.1.0-snapshot/examples/java/tensorflow-model-serving.md)
- [MNIST](https://serving.konduit.ai/0.1.0-snapshot/examples/java/tensorflow-model-serving/tf-mnist_java.md): This page illustrates a simple client-server interaction to perform inference on a TensorFlow model using the Java SDK for Konduit Serving.
- [BERT](https://serving.konduit.ai/0.1.0-snapshot/examples/java/tensorflow-model-serving/tf-bert_java.md): This page illustrates a simple client-server interaction to perform inference on a TensorFlow model using the Java SDK for Konduit Serving.
- [Deeplearning4j (DL4J)](https://serving.konduit.ai/0.1.0-snapshot/examples/java/dl4j_java.md): This document illustrates how to create Konduit Serving configurations with the Java SDK:
- [DataVec](https://serving.konduit.ai/0.1.0-snapshot/examples/java/datavec_java.md): Konduit Serving supports data transformations defined by the DataVec vectorization and ETL library.
- [Open Neural Network Exchange (ONNX)](https://serving.konduit.ai/0.1.0-snapshot/examples/java/onnx_java.md): This page provides a Java example of inferencing  a model, built in Python with ONNX Runtime, a cross-platform, high performance scoring engine for machine learning models.
- [Keras (TensorFlow 2.0)](https://serving.konduit.ai/0.1.0-snapshot/examples/java/keras_java.md): This page illustrates a simple client-server interaction to perform inference on a Keras LSTM model using the Java SDK for Konduit Serving.


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://serving.konduit.ai/0.1.0-snapshot/examples/java.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
