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--- |
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library_name: diffusers |
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license: openrail++ |
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language: |
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- en |
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tags: |
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- text-to-image |
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- stable-diffusion |
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- lora |
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- safetensors |
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- stable-diffusion-xl |
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base_model: Linaqruf/animagine-xl-2.0 |
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widget: |
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- text: face focus, cute, masterpiece, best quality, 1girl, green hair, sweater, looking at viewer, upper body, beanie, outdoors, night, turtleneck |
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parameter: |
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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 |
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example_title: 1girl |
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- text: face focus, bishounen, masterpiece, best quality, 1boy, green hair, sweater, looking at viewer, upper body, beanie, outdoors, night, turtleneck |
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parameter: |
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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 |
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example_title: 1boy |
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--- |
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<style> |
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.title-container { |
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display: flex; |
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flex-direction: column; /* Allow vertical stacking of title and subtitle */ |
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justify-content: center; |
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align-items: center; |
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height: 100vh; |
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background-color: #f5f5f5; |
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} |
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.title { |
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font-size: 2em; |
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text-align: center; |
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color: #333; |
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font-family: 'Verdana', sans-serif; |
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text-transform: uppercase; |
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padding: 1em; |
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box-shadow: 0px 0px 0px rgba(0,0,0,0.1); |
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} |
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.title span { |
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background: -webkit-linear-gradient(45deg, #ff9a9e, #fad0c4, #f6d365); |
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-webkit-background-clip: text; |
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-webkit-text-fill-color: transparent; |
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} |
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.custom-table { |
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table-layout: fixed; |
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width: 100%; |
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border-collapse: collapse; |
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margin-top: 2em; |
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} |
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.custom-table td { |
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width: 50%; |
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vertical-align: top; |
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padding: 10px; |
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box-shadow: 0px 0px 0px 0px rgba(0, 0, 0, 0.15); |
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} |
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.custom-image-container { |
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position: relative; |
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width: 100%; |
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margin-bottom: 0em; |
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overflow: hidden; |
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border-radius: 10px; |
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transition: transform .7s; |
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/* Smooth transition for the container */ |
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} |
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.custom-image-container:hover { |
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transform: scale(1.05); |
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/* Scale the container on hover */ |
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} |
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.custom-image { |
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width: 100%; |
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height: auto; |
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object-fit: cover; |
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border-radius: 10px; |
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transition: transform .7s; |
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margin-bottom: 0em; |
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} |
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.nsfw-filter { |
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filter: blur(8px); /* Apply a blur effect */ |
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transition: filter 0.3s ease; /* Smooth transition for the blur effect */ |
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} |
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.custom-image-container:hover .nsfw-filter { |
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filter: none; /* Remove the blur effect on hover */ |
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} |
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</style> |
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<h1 class="title"> |
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<span>Style Enhancer XL LoRA</span> |
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</h1> |
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<table class="custom-table"> |
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<tr> |
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<td> |
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<div class="custom-image-container"> |
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<img class="custom-image" src="https://cdn-uploads.huggingface.co/production/uploads/6365c8dbf31ef76df4042821/kMqCcN3CpMPHO1qyEgnGk.png" alt="sample1"> |
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</div> |
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<div class="custom-image-container"> |
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<img class="custom-image" src="https://cdn-uploads.huggingface.co/production/uploads/6365c8dbf31ef76df4042821/pfLIDf7ZX6WJHgTlfqiQk.png" alt="sample4"> |
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</div> |
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</td> |
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<td> |
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<div class="custom-image-container"> |
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<img class="custom-image" src="https://cdn-uploads.huggingface.co/production/uploads/6365c8dbf31ef76df4042821/s5ZCIaETb_eKijgbLbXwU.png" alt="sample2"> |
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</div> |
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<div class="custom-image-container"> |
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<img class="custom-image" src="https://cdn-uploads.huggingface.co/production/uploads/6365c8dbf31ef76df4042821/qjC5jKExA_JE5BuQJ6-Ue.png" alt="sample3"> |
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</td> |
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<td> |
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<div class="custom-image-container"> |
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<img class="custom-image nsfw-filter" src="https://cdn-uploads.huggingface.co/production/uploads/6365c8dbf31ef76df4042821/1vvUY1qbgot5np4CPmORh.png" alt="sample1"> |
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</div> |
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<div class="custom-image-container"> |
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<img class="custom-image" src="https://cdn-uploads.huggingface.co/production/uploads/6365c8dbf31ef76df4042821/7OQJdRKKpZponZiZ8cOre.png" alt="sample4"> |
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</div> |
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</td> |
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</tr> |
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</table> |
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<hr> |
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## Overview |
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**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. |
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Example tags include _**face focus, cute, masterpiece, best quality, 1girl, green hair, sweater, looking at viewer, upper body, beanie, outdoors, night, turtleneck**_. |
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<hr> |
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## Model Details |
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- **Developed by:** [Linaqruf](https://github.com/Linaqruf) |
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- **Model type:** LoRA adapter for Stable Diffusion XL |
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- **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. |
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- **License:** [CreativeML Open RAIL++-M License](https://huggingface.co/stabilityai/stable-diffusion-2/blob/main/LICENSE-MODEL) |
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- **Finetuned from model:** [Animagine XL 2.0](https://huggingface.co/Linaqruf/animagine-xl-2.0) |
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<hr> |
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## 🧨 Diffusers Installation |
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Ensure the installation of the latest `diffusers` library, along with other essential packages: |
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```bash |
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pip install diffusers --upgrade |
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pip install transformers accelerate safetensors |
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``` |
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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. |
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```py |
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import torch |
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from diffusers import ( |
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StableDiffusionXLPipeline, |
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EulerAncestralDiscreteScheduler, |
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AutoencoderKL |
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) |
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# Initialize LoRA model and weights |
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lora_model_id = "Linaqruf/style-enhancer-xl-lora" |
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lora_filename = "style-enhancer-xl.safetensors" |
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# Load VAE component |
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vae = AutoencoderKL.from_pretrained( |
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"madebyollin/sdxl-vae-fp16-fix", |
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torch_dtype=torch.float16 |
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) |
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# Configure the pipeline |
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pipe = StableDiffusionXLPipeline.from_pretrained( |
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"Linaqruf/animagine-xl-2.0", |
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vae=vae, |
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torch_dtype=torch.float16, |
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use_safetensors=True, |
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variant="fp16" |
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) |
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pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config) |
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pipe.to('cuda') |
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# Load and fuse LoRA weights |
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pipe.load_lora_weights(lora_model_id, weight_name=lora_filename) |
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pipe.fuse_lora(lora_scale=0.6) |
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# Define prompts and generate image |
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prompt = "face focus, cute, masterpiece, best quality, 1girl, green hair, sweater, looking at viewer, upper body, beanie, outdoors, night, turtleneck" |
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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" |
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image = pipe( |
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prompt, |
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negative_prompt=negative_prompt, |
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width=1024, |
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height=1024, |
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guidance_scale=12, |
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num_inference_steps=50 |
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).images[0] |
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# Unfuse LoRA before saving the image |
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pipe.unfuse_lora() |
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image.save("anime_girl.png") |
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``` |
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