Update README.md

README.md

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+---
+language:
+- en
+base_model:
+- black-forest-labs/FLUX.1-Kontext-dev
+pipeline_tag: image-to-image
+library_name: diffusers
+tags:
+- Style
+- Irasutoya
+- FluxKontext
+- Image-to-Image
+---
+
+# Irasutoya Style LoRA for FLUX.1 Kontext Model
+This repository provides the **Irasutoya** style LoRA adapter for the [FLUX.1 Kontext Model](https://huggingface.co/black-forest-labs/FLUX.1-Kontext-dev).
+This LoRA is part of a collection of 20+ style LoRAs trained on high-quality paired data generated by GPT-4o from the [OmniConsistency](https://huggingface.co/datasets/showlab/OmniConsistency) dataset.
+
+Contributor: Tian YE & Song FEI, HKUST Guangzhou.
+
+## Style Showcase
+Here are some examples of images generated using this style LoRA:
+
+![Irasutoya Style Example](./example-1.png)
+![Irasutoya Style Example](./example-2.png)
+![Irasutoya Style Example](./example-3.png)
+![Irasutoya Style Example](./example-4.png)
+![Irasutoya Style Example](./example-5.png)
+![Irasutoya Style Example](./example-6.png)
+
+## Inference Example
+```python
+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 Irasutoya style directly from the Hub
+pipeline.load_lora_weights("Kontext-Style/Irasutoya_lora", weight_name="Irasutoya_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 = "Irasutoya"
+prompt = f"Turn this image into the Irasutoya 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!