https://github.com/kubeflow/trainer
Distributed ML Training and Fine-Tuning on Kubernetes
https://github.com/kubeflow/trainer
ai distributed fine-tuning gpu huggingface jax kubeflow kubernetes llm machine-learning mlops python pytorch tensorflow xgboost
Last synced: 10 days ago
JSON representation
Distributed ML Training and Fine-Tuning on Kubernetes
- Host: GitHub
- URL: https://github.com/kubeflow/trainer
- Owner: kubeflow
- License: apache-2.0
- Created: 2017-06-28T18:38:14.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2025-03-30T22:35:30.000Z (9 months ago)
- Last Synced: 2025-04-05T19:08:50.104Z (9 months ago)
- Topics: ai, distributed, fine-tuning, gpu, huggingface, jax, kubeflow, kubernetes, llm, machine-learning, mlops, python, pytorch, tensorflow, xgboost
- Language: Python
- Homepage: https://www.kubeflow.org/docs/components/training
- Size: 100 MB
- Stars: 1,747
- Watchers: 79
- Forks: 767
- Open Issues: 142
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Roadmap: ROADMAP.md
Awesome Lists containing this project
README
# Kubeflow Trainer
[](https://www.kubeflow.org/docs/about/community/#kubeflow-slack-channels)
[](https://coveralls.io/github/kubeflow/trainer?branch=master)
[](https://goreportcard.com/report/github.com/kubeflow/trainer)
[](https://www.bestpractices.dev/projects/10435)
[](https://deepwiki.com/kubeflow/trainer)
[](https://app.fossa.com/projects/git%2Bgithub.com%2Fkubeflow%2Ftrainer?ref=badge_shield)
Latest News 🔥
- [2025/09] Kubeflow SDK v0.1 is officially released with support for CustomTrainer,
BuiltinTrainer, and local PyTorch execution. Check out
[the GitHub release notes](https://github.com/kubeflow/sdk/releases/tag/0.1.0).
- [2025/07] PyTorch on Kubernetes: Kubeflow Trainer Joins the PyTorch Ecosystem. Find the
announcement in [the PyTorch blog post](https://pytorch.org/blog/pytorch-on-kubernetes-kubeflow-trainer-joins-the-pytorch-ecosystem/).
- [2025/07] Kubeflow Trainer v2.0 has been officially released. Check out
[the blog post announcement](https://blog.kubeflow.org/trainer/intro/) and [the
release notes](https://github.com/kubeflow/trainer/releases/tag/v2.0.0).
- [2025/04] From High Performance Computing To AI Workloads on Kubernetes: MPI Runtime in
Kubeflow TrainJob. See the [KubeCon + CloudNativeCon London talk](https://youtu.be/Fnb1a5Kaxgo)
## Overview
Kubeflow Trainer is a Kubernetes-native project designed for large language models (LLMs)
fine-tuning and enabling scalable, distributed training of machine learning (ML) models across
various frameworks, including PyTorch, JAX, TensorFlow, and others.
You can integrate other ML libraries such as [HuggingFace](https://huggingface.co),
[DeepSpeed](https://github.com/microsoft/DeepSpeed), or [Megatron-LM](https://github.com/NVIDIA/Megatron-LM)
with Kubeflow Trainer to run them on Kubernetes.
Kubeflow Trainer enables you to effortlessly develop your LLMs with the
[Kubeflow Python SDK](https://github.com/kubeflow/sdk/), and build Kubernetes-native Training
Runtimes using Kubernetes Custom Resource APIs.
## Kubeflow Trainer Introduction
The following KubeCon + CloudNativeCon 2024 talk provides an overview of Kubeflow Trainer capabilities:
[](https://www.youtube.com/watch?v=Lgy4ir1AhYw)
## Getting Started
Please check [the official Kubeflow Trainer documentation](https://www.kubeflow.org/docs/components/trainer/getting-started)
to install and get started with Kubeflow Trainer.
## Community
The following links provide information on how to get involved in the community:
- Join our [`#kubeflow-trainer` Slack channel](https://www.kubeflow.org/docs/about/community/#kubeflow-slack).
- Attend [the bi-weekly AutoML and Training Working Group](https://bit.ly/2PWVCkV) community meeting.
- Check out [who is using Kubeflow Trainer](ADOPTERS.md).
## Contributing
Please refer to the [CONTRIBUTING guide](CONTRIBUTING.md).
## Changelog
Please refer to the [CHANGELOG](CHANGELOG.md).
## Kubeflow Training Operator V1
Kubeflow Trainer project is currently in alpha status, and APIs may change.
If you are using Kubeflow Training Operator V1, please refer [to this migration document](https://www.kubeflow.org/docs/components/trainer/operator-guides/migration/).
Kubeflow Community will maintain the Training Operator V1 source code at
[the `release-1.9` branch](https://github.com/kubeflow/trainer/tree/release-1.9).
You can find the documentation for Kubeflow Training Operator V1 in [these guides](https://www.kubeflow.org/docs/components/trainer/legacy-v1).
## Acknowledgement
This project was originally started as a distributed training operator for TensorFlow and later we
merged efforts from other Kubeflow Training Operators to provide a unified and simplified experience
for both users and developers. We are very grateful to all who filed issues or helped resolve them,
asked and answered questions, and were part of inspiring discussions.
We'd also like to thank everyone who's contributed to and maintained the original operators.
- PyTorch Operator: [list of contributors](https://github.com/kubeflow/pytorch-operator/graphs/contributors)
and [maintainers](https://github.com/kubeflow/pytorch-operator/blob/master/OWNERS).
- MPI Operator: [list of contributors](https://github.com/kubeflow/mpi-operator/graphs/contributors)
and [maintainers](https://github.com/kubeflow/mpi-operator/blob/master/OWNERS).
- XGBoost Operator: [list of contributors](https://github.com/kubeflow/xgboost-operator/graphs/contributors)
and [maintainers](https://github.com/kubeflow/xgboost-operator/blob/master/OWNERS).
- Common library: [list of contributors](https://github.com/kubeflow/common/graphs/contributors) and
[maintainers](https://github.com/kubeflow/common/blob/master/OWNERS).