+++
title = "Reference Overview"
description = "Reference documentation for Kubeflow APIs and services."
weight = 1

+++

<a id="tfjob">
## TFJob

TFJob is a Kubernetes
[custom resource](https://kubernetes.io/docs/concepts/extend-kubernetes/api-extension/custom-resources/)
that you can use to run TensorFlow training jobs on Kubernetes. For help with
using TFJob with Kubeflow, see the [user guide](/docs/components/tftraining/).

API references:

  * [v1](/docs/reference/tfjob/v1/tensorflow/)
  * [v1beta2](/docs/reference/tfjob/v1beta2/tensorflow/)

<a id="pytorchjob">
## PyTorchJob

PyTorchJob is a Kubernetes
[custom resource](https://kubernetes.io/docs/concepts/extend-kubernetes/api-extension/custom-resources/)
that you can use to run PyTorch training jobs on Kubernetes. For help with
using PyTorch with Kubeflow, see the [user guide](/docs/components/pytorch/).

API references:

  * [v1](/docs/reference/pytorchjob/v1/pytorch/)
  * [v1beta2](/docs/reference/pytorchjob/v1beta2/pytorch/)

<a id="metadata">
## Metadata

The goal of the [Metadata](https://github.com/kubeflow/metadata) project is to help Kubeflow users understand and manage their machine learning workflows by tracking and managing the metadata of workflows.

API references:

  * [v1alpha1](/docs/reference/metadata/v1alpha1/kubeflow-metadata-api-spec/)
