cocktailpeanut/fluxgym
Dead simple FLUX LoRA training UI with LOW VRAM support observed · 2026-08-28
Health v2 · maintenance only
65/100
- Activity 94
- Release rhythm 35
- Longevity 51
Flags: no_releases
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 727
- days_rel: n/a
- days_push: 36
- n_releases_24m: 0
Adoption not part of the score
3246 stars · 371 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
FluxGym is a simple web UI for training FLUX LoRA models with low VRAM support (12GB/16GB/20GB). It combines the AI-Toolkit Gradio frontend with Kohya sd-scripts as the training backend.
Use cases
- train a flux lora with a simple ui
- fine-tune flux on low vram gpu
- train image model lora without command line
- train custom character lora for stable diffusion
- publish trained lora to huggingface
When to choose
- you have 12-20GB VRAM and want to train FLUX LoRAs
- you want a simple UI over Kohya sd-scripts
- you want automatic model downloads and Huggingface publishing
When to avoid
- you need to train models other than FLUX-family image models
- you need multi-GPU or large-scale training infrastructure
- you prefer fully scriptable headless training pipelines
Facets
application · maturity active
machine-learning llm-training gui image-processing machine-learning image-processing artificial-intelligence python self-hosted cross-platform flux lora-training stable-diffusion gradio low-vram kohya fine-tuning webui docker gpu
1 source
- readme: https://github.com/cocktailpeanut/fluxgym · fetched 2026-08-28 · 2eda75279588
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| cocktailpeanut/fluxgym | main | 65 |
For agents
markdown · JSON · MCP: product_card(name="cocktailpeanut/fluxgym")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem