--- 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 Enhancer XL LoRA

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## Overview **Style Enhancer XL LoRA** is an advanced, high-resolution LoRA (Low-Rank Adaptation) adapter designed to enhance the capabilities of Animagine XL 2.0. This innovative model excels in fine-tuning and refining anime-style images, producing unparalleled quality and detail. It seamlessly integrates with the Stable Diffusion XL framework, and uniquely supports Danbooru tags for precise and creative image generation. Example tags include _**face focus, cute, masterpiece, best quality, 1girl, green hair, sweater, looking at viewer, upper body, beanie, outdoors, night, turtleneck**_.
## Model Details - **Developed by:** [Linaqruf](https://github.com/Linaqruf) - **Model type:** LoRA adapter for Stable Diffusion XL - **Model Description:** A compact yet powerful adapter designed to augment and enhance the output of large models like Animagine XL 2.0. This adapter not only improves the style and quality of anime-themed images but also allows users to recreate the distinct 'old-school' art style of SD 1.5. It's the perfect tool for generating high-fidelity, anime-inspired visual content. - **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)
## 🧨 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 Style Enhancer XL 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/style-enhancer-xl-lora" lora_filename = "style-enhancer-xl.safetensors" # 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=0.6) # 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") ```