# Examples

To see MLServer in action you can check out the examples below. These are end-to-end notebooks, showing how to serve models with MLServer.

## Inference Runtimes

If you are interested in how MLServer interacts with particular model frameworks, you can check the following examples. These focus on showcasing the different [inference runtimes](https://github.com/SeldonIO/MLServer/blob/master/docs-gb/runtimes/index.md) that ship with MLServer out of the box. Note that, for **advanced use cases**, you can also write your own custom inference runtime (see the [example below on custom models](https://docs.seldon.ai/mlserver/examples/custom)).

* [Serving Scikit-Learn models](https://docs.seldon.ai/mlserver/examples/sklearn)
* [Serving XGBoost models](https://docs.seldon.ai/mlserver/examples/xgboost)
* [Serving LightGBM models](https://docs.seldon.ai/mlserver/examples/lightgbm)
* [Serving CatBoost models](https://github.com/SeldonIO/MLServer/blob/master/docs-gb/examples/catboost/README.md)
* [Serving MLflow models](https://docs.seldon.ai/mlserver/examples/mlflow)
* [Serving custom models](https://docs.seldon.ai/mlserver/examples/custom)
* [Serving Alibi Detect models](https://docs.seldon.ai/mlserver/examples/alibi-detect)
* [Serving HuggingFace models](https://docs.seldon.ai/mlserver/examples/huggingface)

## MLServer Features

To see some of the advanced features included in MLServer (e.g. multi-model serving), check out the examples below.

* [Multi-Model Serving with multiple frameworks](https://docs.seldon.ai/mlserver/examples/mms)
* [Loading / unloading models from a model repository](https://docs.seldon.ai/mlserver/examples/model-repository)
* [Content-Type Decoding](https://docs.seldon.ai/mlserver/examples/content-type)
* [Custom Conda environment](https://docs.seldon.ai/mlserver/examples/conda)
* [Serving custom models requiring JSON inputs or outputs](https://docs.seldon.ai/mlserver/examples/custom-json)
* [Serving models through Kafka](https://docs.seldon.ai/mlserver/examples/kafka)
* [Streaming inference](https://docs.seldon.ai/mlserver/examples/streaming)

## Tutorials

Tutorials are designed to be *beginner-friendly* and walk through accomplishing a series of tasks using MLServer (and other tools).

* [Deploying a Custom Tensorflow Model with MLServer and Seldon Core](https://docs.seldon.ai/mlserver/examples/cassava)