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Viko010285/Ghibli_lora
Ghibli_lora is a image-to-image model from Viko010285. Use it when you need one image transformed into another. It is set up for diffusers.
This repository provides the Ghibli style LoRA adapter for the FLUX.1 Kontext Model. This LoRA is part of a collection of 20+ style LoRAs trained on high-quality paired data generated by GPT-4o from the OmniConsistenc…
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.safetensors359 MB · 95%
From the Hugging Face model README
This repository provides the Ghibli style LoRA adapter for the FLUX.1 Kontext Model. This LoRA is part of a collection of 20+ style LoRAs trained on high-quality paired data generated by GPT-4o from the OmniConsistency dataset.
Contributor: Tian YE & Song FEI, HKUST Guangzhou.
Here are some examples of images generated using this style LoRA:

from diffusers import FluxKontextPipeline
from diffusers.utils import load_image
import torch
# Load the base pipeline
pipeline = FluxKontextPipeline.from_pretrained(
"black-forest-labs/FLUX.1-Kontext-dev",
torch_dtype=torch.bfloat16
).to('cuda')
# Load the LoRA adapter for the Ghibli style directly from the Hub
pipeline.load_lora_weights("Kontext-Style/Ghibli_lora", weight_name="Ghibli_lora_weights.safetensors", adapter_name="lora")
pipeline.set_adapters(["lora"], adapter_weights=[1])
# Load a source image (you can use any image)
image = load_image("https://huggingface.co/datasets/black-forest-labs/kontext-bench/resolve/main/test/images/0003.jpg").resize((1024, 1024))
# Prepare the prompt
# The style_name is used in the prompt and for the output filename.
style_name = "Ghibli"
prompt = f"Turn this image into the Ghibli style."
# Run inference
result_image = pipeline(
image=image,
prompt=prompt,
height=1024,
width=1024,
num_inference_steps=24
).images[0]
# Save the result
output_filename = f"{style_name.replace(' ', '_')}.png"
result_image.save(output_filename)
print(f"Image saved as {output_filename}")
Feel free to open an issue or contact us for feedback or collaboration!