diffusers-modular/flux3-tarot-lora

FLUX.3 Tarot LoRA

A Rider-Waite tarot-style DreamBooth LoRA for the FLUX.3 image (klein) model, trained with the diffusers DreamBooth FLUX.3 trainer. Trigger the style with trtcrd, e.g. "a trtcrd of ..., tarot style".

Prompt

a trtcrd of a person giving a talk on a stage under a glowing emblem, "the speaker" arcana, tarot style

Prompt

a trtcrd of a man carving meat from a tall vertical rotisserie that reads "Döner", "the carver" arcana, tarot style

Prompt

a trtcrd of a dog eating a big bowl of spaghetti at a dinner table, "the glutton" arcana, tarot style

Prompt

a trtcrd of an astronaut planting a flag on a tiny planet among stars, "the explorer" arcana, tarot style

Inference

import torch
from diffusers.modular_pipelines import Flux3AutoBlocks

pipe = Flux3AutoBlocks().init_pipeline("black-forest-labs/flux-3-image-klein-base")
pipe.load_components(dtype=torch.bfloat16)
pipe.to("cuda")
pipe.load_lora_weights("diffusers-modular/flux3-tarot-lora", weight_name="pytorch_lora_weights.safetensors")

image = pipe(
    prompt="a trtcrd of a dog eating a big bowl of spaghetti, tarot style",
    height=1344, width=800, num_inference_steps=28, negative_prompt="",
    max_sequence_length=512, text_encoder_out_layers=(4, 8, 12, 16, 20, 24, 28, 32),
    output="images",
)[0]
image.save("tarot.png")

Trigger

Use trtcrd in the prompt: "a trtcrd of {your subject}, tarot style".

Training

• Base model: black-forest-labs/flux-3-image-klein-base
• Dataset: multimodalart/1920-raider-waite-tarot-public-domain
• 1500 steps · seed 0 · resolution 1024 · aspect-ratio buckets
• Default weights (pytorch_lora_weights.safetensors): AdamW (8-bit), rank 16, lr 1e-4

Sweep variants

This repo also includes the configs from a small sweep (one setting changed vs the default). Load one with weight_name="<folder>/pytorch_lora_weights.safetensors":

variant	change	weight_name
default	AdamW, rank 16	pytorch_lora_weights.safetensors
rank 8	rank → 8	rank8/pytorch_lora_weights.safetensors
rank 32	rank → 32	rank32/pytorch_lora_weights.safetensors
more layers	+ modulation layers	more-layers/pytorch_lora_weights.safetensors
prodigy	Prodigy optimizer, lr 1	prodigy/pytorch_lora_weights.safetensors