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Add Kubeflow Website links to README
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andreyvelich committed Jan 11, 2024
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23 changes: 15 additions & 8 deletions README.md
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## Overview

Starting from v1.3, this training operator provides Kubernetes custom resources that makes it easy to
run distributed or non-distributed TensorFlow/PyTorch/Apache MXNet/XGBoost/MPI jobs on Kubernetes.
Kubeflow Training Operator is a Kubernetes-native project for fine-tuning and
scalable distributed training of machine learning (ML) models created with various ML frameworks
such as PyTorch, Tensorflow, XGBoost, MPI, Paddle and others.

> Note: Before v1.2 release, Kubeflow Training Operator only supports TFJob on Kubernetes.
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## Prerequisites

- Version >= 1.23 of Kubernetes cluster and `kubectl`
- Version >= 1.25 of Kubernetes cluster and `kubectl`

## Installation

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### Stable Release

```bash
kubectl apply -k "github.com/kubeflow/training-operator/manifests/overlays/standalone?ref=v1.5.0"
kubectl apply -k "github.com/kubeflow/training-operator/manifests/overlays/standalone?ref=v1.7.0"
```

### TensorFlow Release Only
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### Python SDK for Kubeflow Training Operator

Training Operator provides Python SDK for the custom resources. More docs are available in [sdk/python](sdk/python) folder.
Training Operator provides Python SDK for the custom resources. For the APIs check
[the SDK `TrainingClient`](sdk/python/kubeflow/training/api/training_client.py).

Use `pip install` command to install the latest release of the SDK:

```
pip install kubeflow-training
```

## Quick Start
Training Operator controller and Python SDK have the same release versions.

Please refer to the [quick-start-v1.md](docs/quick-start-v1.md) and [Kubeflow Training User Guide](https://www.kubeflow.org/docs/guides/components/tftraining/) for more information.
## Quickstart

Please refer to the [getting started guide](https://www.kubeflow.org/docs/components/training/overview/#getting-started)
to quickly create your first Training Operator Job.

## API Documentation

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| `v1.3.x` | `v1` | 1.18+ |
| `v1.4.x` | `v1` | 1.23+ |
| `v1.5.x` | `v1` | 1.23+ |
| `latest` (master HEAD) | `v1` | 1.23+ |
| `v1.6.x` | `v1` | 1.23+ |
| `v1.7.x` | `v1` | 1.25+ |
| `latest` (master HEAD) | `v1` | 1.25+ |

## Acknowledgement

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