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.
Training at fal.ai
Training was done using fal.ai/models/fal-ai/flux-kontext-trainer/playground.
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Base model
black-forest-labs/FLUX.1-Kontext-dev