bghira/SimpleTuner

Health v2 · maintenance only

Adoption not part of the score

2940 stars · 294 forks observed · 2026-10-17

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

SimpleTuner is a Python fine-tuning toolkit for image, video, and audio diffusion models built on Hugging Face Diffusers. It provides a web UI and CLI for training models like Stable Diffusion and Flux with support for distributed and memory-constrained setups.

Use cases

• fine-tune stable diffusion on my own images
• train a custom flux model checkpoint
• fine-tune a video diffusion model
• train stable diffusion xl on a small dataset
• run distributed multi-node diffusion training
• offload optimizer states on low-VRAM GPUs
• create a LoRA for image generation

When to choose

• you want to fine-tune diffusion models for image, video, or audio generation
• you need proven training features with sensible defaults
• you want a web UI or CLI to manage the training lifecycle
• you need distributed or memory-efficient training via DeepSpeed or FSDP2

When to avoid

• you need to train non-diffusion models like LLMs or classifiers
• you want a no-code hosted training service
• you need inference-only image generation without training

Facets

library · maturity active

llm-training machine-learning deep-learning gpu-computing machine-learning deep-learning image-processing artificial-intelligence python cli diffusion-models stable-diffusion flux fine-tuning diffusers pytorch training-toolkit web-ui distributed-training deepspeed fsdp video audio gpu linux docker

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