OneTrainer
NerogarOneTrainer is a training application for diffusion models, supporting full fine-tuning, LoRA and embeddings across Stable Diffusion 1.5 through 3.5, SDXL, FLUX.1, FLUX.2, Qwen Image, PixArt, Sana and Hunyuan Video. It includes masked training, EMA, aspect-ratio bucketing and multi-resolution training, and runs from either a GUI or a CLI.
Openness
5 high confidence- license
- AGPL-3.0(OSI)
- source
- public(Nerogar/OneTrainer)
- core features withheld
- no — no enterprise or ee path in the repository root and no paid tier described in the README
OneTrainer is licensed under AGPL-3.0, an OSI-approved license, and the full source ships in this repository. The repository has no enterprise or paid-tier path, so nothing is withheld from what is published.
- https://raw.githubusercontent.com/Nerogar/OneTrainer/master/LICENSE.txt recorded 2026-10-06
LICENSE.txt body, read in full: the stock GNU AGPL v3 text, carrying no appended term or additional condition.
- https://raw.githubusercontent.com/Nerogar/OneTrainer/master/README.md recorded 2026-10-06
README, read for the distribution and gating question: it describes installing and running the code from this repository and names no enterprise, paid or licence-gated build.
Adoption
2 low confidenceNo package registry carries OneTrainer, so GitHub stars are the only adoption signal available. A star reflects attention rather than actual use, which is why this reading carries low confidence.
- https://api.github.com/repos/Nerogar/OneTrainer recorded 2026-08-31
Repo metadata for Nerogar/OneTrainer: stargazers_count 3192, archived false, pushed_at 2026-08-24.
Capability
3 medium confidenceOneTrainer and ai-toolkit trade off as the category's diffusion-trainer pair: OneTrainer reaches further on method, with full fine-tuning and embeddings rather than only adapters, while ai-toolkit covers more modalities, including video and audio. Neither has a distributed-training story, which keeps both below the tools with wider training-scale claims.
- https://raw.githubusercontent.com/Nerogar/OneTrainer/master/README.md recorded 2026-10-07
Features section lists supported models from Ernie Image and Z-Image through SD 1.5-3.5, SDXL, FLUX.1, Flux.2 Dev and Klein, PixArt, Sana and Hunyuan Video; training methods full fine-tuning, LoRA and embeddings; and masked training, automatic backups, image augmentation, TensorBoard, EMA with CPU offload, aspect-ratio bucketing and multi-resolution training.
Verified 2026-09-27