Kontext Style Loras

🚀 FLUX.1 Kontext模型风格LoRA适配器

本仓库为FLUX.1 Kontext模型提供了20多种风格的LoRA适配器，能够实现多种艺术和卡通风格的高质量图像到图像生成。这些LoRA是在由GPT - 4o生成的高质量配对数据上进行训练的。数据来源于Omniconsistency。

语言与模型信息

🚀 快速开始

本仓库提供了一系列风格的LoRA适配器，可用于为FLUX.1 Kontext模型赋予多种艺术和卡通风格，实现高质量的图像到图像生成。

✨ 主要特性

• 提供20多种风格的LoRA适配器，可实现多种艺术和卡通风格的图像生成。
• LoRA适配器在由GPT - 4o生成的高质量配对数据上训练。
• 数据来源于Omniconsistency。

最新消息！

我们创建了[Kontext - Style](https://huggingface.co/Kontext - Style)来为每个LoRA单独建立仓库！并且我们提供了[空间演示](https://huggingface.co/spaces/Kontext - Style/Kontext - Style - LoRAs)，可以直接在线运行我们的LoRA！

贡献者：香港科技大学（广州）的叶天和费松。

💻 使用示例

基础用法

from huggingface_hub import hf_hub_download
from diffusers import FluxKontextPipeline
from diffusers.utils import load_image
import torch

STYLE_NAME = "3D_Chibi"

style_type_lora_dict = {
    "3D_Chibi": "3D_Chibi_lora_weights.safetensors",
    "American_Cartoon": "American_Cartoon_lora_weights.safetensors",
    "Chinese_Ink": "Chinese_Ink_lora_weights.safetensors",
    "Clay_Toy": "Clay_Toy_lora_weights.safetensors",
    "Fabric": "Fabric_lora_weights.safetensors",
    "Ghibli": "Ghibli_lora_weights.safetensors",
    "Irasutoya": "Irasutoya_lora_weights.safetensors",
    "Jojo": "Jojo_lora_weights.safetensors",
    "Oil_Painting": "Oil_Painting_lora_weights.safetensors",
    "Pixel": "Pixel_lora_weights.safetensors",
    "Snoopy": "Snoopy_lora_weights.safetensors",
    "Poly": "Poly_lora_weights.safetensors",
    "LEGO": "LEGO_lora_weights.safetensors",
    "Origami" : "Origami_lora_weights.safetensors",
    "Pop_Art" : "Pop_Art_lora_weights.safetensors",
    "Van_Gogh" : "Van_Gogh_lora_weights.safetensors",
    "Paper_Cutting" : "Paper_Cutting_lora_weights.safetensors",
    "Line" : "Line_lora_weights.safetensors",
    "Vector" : "Vector_lora_weights.safetensors",
    "Picasso" : "Picasso_lora_weights.safetensors",
    "Macaron" : "Macaron_lora_weights.safetensors",
    "Rick_Morty" : "Rick_Morty_lora_weights.safetensors"
}


hf_hub_download(repo_id="Owen777/Kontext-Style-Loras", filename=style_type_lora_dict[STYLE_NAME], local_dir="./LoRAs")
image = load_image("https://huggingface.co/datasets/black-forest-labs/kontext-bench/resolve/main/test/images/0003.jpg").resize((1024, 1024))
image.save("0037.png")
pipeline = FluxKontextPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights(f"./LoRAs/{style_type_lora_dict[STYLE_NAME]}", adapter_name="lora")
pipeline.set_adapters(["lora"], adapter_weights=[1])
image = pipeline(image=image, prompt=f"Turn this image into the {STYLE_NAME.replace('_', ' ')} style.",height=1024,width=1024,num_inference_steps=24).images[0]
image.save(f"{STYLE_NAME}.png")

如果您有任何反馈或合作需求，欢迎提出问题或与我们联系！我们将尽快发布更多风格的LoRA适配器！