Kontext Style Loras

🚀 FLUX.1 Kontext模型風格LoRA適配器

本倉庫為FLUX.1 Kontext模型提供了20多種風格的LoRA適配器，能夠實現多種藝術和卡通風格的高質量圖像到圖像生成。這些LoRA是在由GPT - 4o生成的高質量配對數據上進行訓練的。數據來源於Omniconsistency。

語言與模型信息

🚀 快速開始

本倉庫提供了一系列風格的LoRA適配器，可用於為FLUX.1 Kontext模型賦予多種藝術和卡通風格，實現高質量的圖像到圖像生成。

✨ 主要特性

• 提供20多種風格的LoRA適配器，可實現多種藝術和卡通風格的圖像生成。
• LoRA適配器在由GPT - 4o生成的高質量配對數據上訓練。
• 數據來源於Omniconsistency。

最新消息！

我們創建了[Kontext - Style](https://huggingface.co/Kontext - Style)來為每個LoRA單獨建立倉庫！並且我們提供了[空間演示](https://huggingface.co/spaces/Kontext - Style/Kontext - Style - LoRAs)，可以直接在線運行我們的LoRA！

貢獻者：香港科技大學（廣州）的葉天和費松。

💻 使用示例

基礎用法

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")

如果您有任何反饋或合作需求，歡迎提出問題或與我們聯繫！我們將盡快發佈更多風格的LoRA適配器！