Image-to-Image
Diffusers
flux
lora
fal
How to use from the
Use from the
Diffusers library
pip install -U diffusers transformers accelerate
import torch
from diffusers import DiffusionPipeline
from diffusers.utils import load_image

# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", dtype=torch.bfloat16, device_map="cuda")
pipe.load_lora_weights("gokaygokay/Rotation-Fix-Kontext-Dev-LoRA")

prompt = "Fix rotation and fill background"
input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png")

image = pipe(image=input_image, prompt=prompt).images[0]

Rotation Fix Kontext Dev LoRA

Prompt
Fix rotation and fill background
Prompt
Fix rotation and fill background

Model description

Trigger phrase

Fix rotation and fill background

Download model

Weights for this model are available in Safetensors format.

Download

Training at fal.ai

Training was done using fal.ai/models/fal-ai/flux-kontext-trainer/playground.

Citation and attribution

This model release is maintained by Gökay Aydoğan. If you reference this repository in academic work, please cite it as follows and also cite the upstream models, datasets, or projects it builds upon.

@software{aydogan2025rotation_fix_kontext_dev_lora,
  author = {Aydoğan, Gökay},
  title = {{Rotation-Fix-Kontext-Dev-LoRA}},
  year = {2025},
  publisher = {Hugging Face},
  url = {https://huggingface.co/gokaygokay/Rotation-Fix-Kontext-Dev-LoRA},
  note = {Model repository; cite the base model and upstream datasets as required.}
}
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