Add FLUX.3 tarot LoRA sweep + model card

.gitattributes

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+images/carver.jpg filter=lfs diff=lfs merge=lfs -text
+images/explorer.jpg filter=lfs diff=lfs merge=lfs -text
+images/glutton.jpg filter=lfs diff=lfs merge=lfs -text
+images/speaker.jpg filter=lfs diff=lfs merge=lfs -text

README.md

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+---
+base_model: black-forest-labs/flux-3-image-klein-base
+library_name: diffusers
+license: other
+tags:
+- flux3
+- lora
+- diffusers
+- text-to-image
+- tarot
+instance_prompt: a trtcrd, tarot style
+widget:
+- text: a trtcrd of a person giving a talk on a stage under a glowing emblem, tarot style
+  output:
+    url: images/speaker.jpg
+- text: a trtcrd of a man carving meat from a Döner rotisserie, tarot style
+  output:
+    url: images/carver.jpg
+- text: a trtcrd of a dog eating a big bowl of spaghetti at a dinner table, tarot style
+  output:
+    url: images/glutton.jpg
+- text: a trtcrd of an astronaut planting a flag on a tiny planet among stars, tarot style
+  output:
+    url: images/explorer.jpg
+---
+
+# 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"`.
+
+<Gallery />
+
+## Inference
+
+```python
+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](https://huggingface.co/datasets/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` |

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