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SimpleTuner

bghira/SimpleTuner

A Python-based general fine-tuning kit for image/video/audio diffusion models

GitHub

GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026

65views this month

2.9k stars294 forksLast push Sep 7, 2026 Python AGPL-3.0

Decision brief

SimpleTuner is a Python-based tool for fine-tuning diffusion models used in machine learning tasks such as image, video, and audio processing. It offers utilities and scripts to streamline the process.

Good fit when

Use SimpleTuner when you need specialized fine-tuning capabilities for diffusion models involving image, video, or audio data.
Consider it if your project is licensed in a manner that is compatible with AGPL-3.0, benefiting from its open-source community and contributions.

Avoid when

Do not use SimpleTuner if your project requires proprietary licensing, since it is released under AGPL-3.0 which may impose conditions that could be incompatible with commercial projects.
Avoid SimpleTuner for tasks unrelated to diffusion models such as natural language processing, as it was designed specifically for image, video, and audio data.

Requirements:: SimpleTuner does not have a stated requirement for Docker, making deployment more flexible.

Observed Jul 14, 2026 · Source: enrich:decision_facts

SimpleTuner alternatives Trust report

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Maintenance and security

Full trust report

Maintenance: Active (12d since push); As of Sep 19, 2026
Provenance: Not a fork · Personal account; As of Sep 19, 2026
Security (OSV): No lockfile; As of Jul 11, 2026

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

Install

pip install SimpleTuner

PyPI

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Evidence and technical details

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

Overview

SimpleTuner provides utilities and scripts to facilitate the fine-tuning process of various diffusion models related to machine learning tasks including image, video, and audio processing.

Capability facts

Deploy: Self-host
Source: dockerfile:Dockerfile · Sep 19, 2026
Docker: Dockerfile present
Source: dockerfile:Dockerfile · Sep 19, 2026
CLI: CLI entrypoint
Source: pyproject.toml:[project.scripts] · Sep 19, 2026
MCP server: No MCP server detected
Source: repo_scan · Sep 19, 2026
Languages: python, javascript
Source: github.language+package.json+pyproject.toml · Sep 19, 2026

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

Python runtimePython

Source: README excerpt (regex_v1, Sep 19, 2026)

pip install simpletuner

Source link

README

General Requirements NVIDIA : RTX 3080+ recommended (tested up to H200) AMD : 7900 XTX 24GB and MI300X verified (higher memory usage vs NVIDIA) Apple : M3 Max+ with 24GB+ unified memory for LoRA training Base installation (CPU only PyTorch) pip install simpletuner

For agents

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

/tools/bghira-simpletuner.md GET /api/graphcanon/tools/bghira-simpletuner GET /api/graphcanon/graph?tool=bghira-simpletuner