Flux 3 Klein Image LoRA Training
Collection
Experimental training adapter and logs for Flux 3 Klein Image • 9 items • Updated
How to use SimpleTuner/flux-3-klein-image-LoRA-experiments with Diffusers:
pip install -U diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("black-forest-labs/flux-3-image-klein-base", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("SimpleTuner/flux-3-klein-image-LoRA-experiments")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]This journal follows three FLUX.3 Klein training experiments: learning Domokun at different resolutions, training a broad-data assistant LoRA, and using that assistant to finetune distilled Klein on photographic data.
The recipes build on the Qwen Image 2.1 experiments and their v3 training assistant.
Each chapter includes its settings, checkpoint links, and previews. The complete recipes and run manifest are available alongside them.
All eight runs completed. Final adapters and validation images are uploaded.
| Run | Final updates | Checkpoints | Final adapter |
|---|---|---|---|
| Domokun, 512px | 10,000 | 20 | Weights |
| Domokun, 1024px | 10,000 | 20 | Weights |
| Domokun, mixed 512px + 1024px | 10,000 | 20 | Weights |
| Training assistant | 30,000 | 30 | Weights |
| Photo 512px, native SDPA | 50,000 | 50 | Weights |
| Photo 1024px, native SDPA | 50,000 | 50 | Weights |
| Photo 512px, Kohaku-FA | 50,000 | 50 | Weights |
| Photo 1024px, Kohaku-FA | 50,000 | 50 | Weights |
Hub checkpoints verified 2026-10-17.
Base model
black-forest-labs/flux-3-image-klein