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---
library_name: diffusers
license: openrail++
language:
- en
tags:
- text-to-image
- stable-diffusion
- lora
- safetensors
- stable-diffusion-xl
base_model: Linaqruf/animagine-xl-2.0
widget:
- text: face focus, cute, masterpiece, best quality, 1girl, green hair, sweater, looking at viewer, upper body, beanie, outdoors, night, turtleneck
parameter:
negative_prompt: lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry
example_title: 1girl
- text: face focus, bishounen, masterpiece, best quality, 1boy, green hair, sweater, looking at viewer, upper body, beanie, outdoors, night, turtleneck
parameter:
negative_prompt: lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry
example_title: 1boy
---
<style>
body {
font-family: 'Verdana', sans-serif;
background-color: #f5f5f5;
margin: 0;
padding: 0;
}
.title-container {
display: flex;
flex-direction: column;
justify-content: center;
align-items: center;
height: 100vh;
background-color: #f5f5f5;
}
.title {
font-size: 3em;
text-align: center;
color: #333;
text-transform: uppercase;
padding: 0.5em;
font-weight: bold;
}
.title span {
background: -webkit-linear-gradient(45deg, #ff9a9e, #fad0c4, #f6d365);
-webkit-background-clip: text;
-webkit-text-fill-color: transparent;
}
.gallery-container {
max-width: 90%;
margin: 20px auto;
text-align: center;
position: relative;
}
.gallery-radio {
display: none;
}
.gallery-image {
display: none;
width: 100%;
margin: 20px auto;
transition: opacity 0.3s ease;
}
.gallery-image img {
width: 100%;
height: auto;
border-radius: 10px;
transition: transform 0.3s ease;
}
.gallery-image img:hover {
transform: scale(1.05);
}
#radio1:checked ~ #image1,
#radio2:checked ~ #image2,
#radio3:checked ~ #image3 {
display: block;
}
.btn {
display: inline-block;
padding: 10px 20px;
margin: 10px;
background: linear-gradient(135deg, #6e8efb, #a777e3);
color: white;
border: none;
border-radius: 25px;
cursor: pointer;
text-decoration: none;
transition: all 0.7s ease;
box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
text-shadow: 0 1px 1px rgba(0, 0, 0, 0.2);
font-weight: bold;
}
.btn:hover, .btn:focus {
background: linear-gradient(135deg, #5b7de2, #8561c5);
box-shadow: 0 5px 15px rgba(0, 0, 0, 0.2);
}
.btn:active {
transform: translateY(1px);
box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
}
</style>
<h1 class="title">
<span>Anime Detailer XL LoRA</span>
</h1>
<div class="gallery-container">
<input type="radio" name="gallery" id="radio1" class="gallery-radio" aria-label="Less Detail">
<input type="radio" name="gallery" id="radio2" class="gallery-radio" checked aria-label="Normal">
<input type="radio" name="gallery" id="radio3" class="gallery-radio" aria-label="More Detail">
<label for="radio1" class="btn">Less Detail</label>
<label for="radio2" class="btn">Normal</label>
<label for="radio3" class="btn">More Detail</label>
<!-- Image Gallery -->
<div id="image1" class="gallery-image">
<img src="https://cdn-uploads.huggingface.co/production/uploads/6365c8dbf31ef76df4042821/RFtKV5Q6-8pWRzUA7AjOw.png" alt="sample1" loading="lazy">
</div>
<div id="image2" class="gallery-image">
<img src="https://cdn-uploads.huggingface.co/production/uploads/6365c8dbf31ef76df4042821/8_Z2IYeTOYJAMuFyJBRwX.png" alt="sample2" loading="lazy">
</div>
<div id="image3" class="gallery-image">
<img src="https://cdn-uploads.huggingface.co/production/uploads/6365c8dbf31ef76df4042821/0CyCkmFrWjPaBNLAwKMq8.png" alt="sample3" loading="lazy">
</div>
</div>
## Overview
**Anime Detailer XL LoRA** is a cutting-edge LoRA adapter designed to work alongside Animagine XL 2.0. This unique model specializes in concept modulation, enabling users to adjust the level of detail in generated anime-style images. By manipulating a concept slider, users can create images ranging from highly detailed to more abstract representations.
<hr>
## Model Details
- **Developed by:** [Linaqruf](https://github.com/Linaqruf)
- **Model type:** LoRA adapter for Stable Diffusion XL
- **Model Description:** This adapter is a concept slider, allowing users to control the level of detail in anime-themed images. The closer the slider is set to 2, the more detailed the result; closer to -2, the less detailed. It is a versatile tool for artists and creators seeking various artistic expressions within anime imagery.
- **License:** [CreativeML Open RAIL++-M License](https://huggingface.co/stabilityai/stable-diffusion-2/blob/main/LICENSE-MODEL)
- **Finetuned from model:** [Animagine XL 2.0](https://huggingface.co/Linaqruf/animagine-xl-2.0)
<hr>
## 🧨 Diffusers Installation
Ensure the installation of the latest `diffusers` library, along with other essential packages:
```bash
pip install diffusers --upgrade
pip install transformers accelerate safetensors
```
The following Python script demonstrates how to utilize the LoRA with Animagine XL 2.0. The default scheduler is EulerAncestralDiscreteScheduler, but it can be explicitly defined for clarity.
```py
import torch
from diffusers import (
StableDiffusionXLPipeline,
EulerAncestralDiscreteScheduler,
AutoencoderKL
)
# Initialize LoRA model and weights
lora_model_id = "Linaqruf/anime-slider-xl-lora"
lora_filename = "anime-slider-xl.safetensors"
lora_scale_slider = 2 # -2 for less detailed result
# Load VAE component
vae = AutoencoderKL.from_pretrained(
"madebyollin/sdxl-vae-fp16-fix",
torch_dtype=torch.float16
)
# Configure the pipeline
pipe = StableDiffusionXLPipeline.from_pretrained(
"Linaqruf/animagine-xl-2.0",
vae=vae,
torch_dtype=torch.float16,
use_safetensors=True,
variant="fp16"
)
pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
pipe.to('cuda')
# Load and fuse LoRA weights
pipe.load_lora_weights(lora_model_id, weight_name=lora_filename)
pipe.fuse_lora(lora_scale=lora_scale_slider)
# Define prompts and generate image
prompt = "face focus, cute, masterpiece, best quality, 1girl, green hair, sweater, looking at viewer, upper body, beanie, outdoors, night, turtleneck"
negative_prompt = "lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry"
image = pipe(
prompt,
negative_prompt=negative_prompt,
width=1024,
height=1024,
guidance_scale=12,
num_inference_steps=50
).images[0]
# Unfuse LoRA before saving the image
pipe.unfuse_lora()
image.save("anime_girl.png")
```
## Acknowledgements
Our project has been enriched by the following significant works:
- **[Erasing Concepts from Diffusion Models](https://github.com/rohitgandikota/erasing)** by Rohit Gandikota et al.
- **[LECO](https://github.com/p1atdev/LECO)** by p1atdev.
- **[AI Toolkit](https://github.com/ostris/ai-toolkit)** by Ostris.
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