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trainer

kubeflow/trainer

Distributed AI Model Training and LLM Fine-Tuning on Kubernetes

GitHub Website

GraphCanon updated 4w · GitHub synced 4w

2.2k stars995 forksLast push 4w Go Apache-2.0

Decision brief

Trainer is built for orchestrating distributed machine learning workflows specifically in Kubernetes environments and supports major frameworks including TensorFlow, PyTorch, and Hugging Face models.

Good fit when

You need to fine-tune large language models or orchestrate complex training workflows across multiple nodes on a Kubernetes cluster.
Your infrastructure is already built around Kubernetes for scalability and automation, making Trainer an ideal fit for integrating distributed AI tasks.

Avoid when

If your setup does not have a Kubernetes environment configured, as this could require significant changes in infrastructure to start using trainer efficiently.
When you plan to implement your model training within another container orchestration system, such as Docker Swarm or Amazon ECS, since Trainer is optimized for operation with Kubernetes.

Requirements:: Min 8 GB RAM

Observed Jul 14, 2026 · Source: enrich:decision_facts

trainer alternatives Trust report

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Maintenance and security

Full trust report

Maintenance: Very active (0d since push); As of 4w
Provenance: Not a fork · Organization account; As of 4w
Security (OSV): No lockfile; As of 1mo

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

go get github.com/kubeflow/trainer

pkg.go.dev

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Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

A repository for orchestrating distributed machine learning workflows with support for various frameworks like TensorFlow, PyTorch, Hugging Face models, among others, specifically designed for Kubernetes environments.

Capability facts

Languages: go
Source: github.language · Jul 24, 2026

README

Getting Started

Please check the official Kubeflow Trainer documentation to install and get started with Kubeflow Trainer.

For agents

This page has a .md twin and JSON over the API.

/tools/kubeflow-trainer.md GET /api/graphcanon/tools/kubeflow-trainer GET /api/graphcanon/graph?tool=kubeflow-trainer