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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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body { |
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font-family: 'Verdana', sans-serif; |
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background-color: #f5f5f5; |
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margin: 0; |
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padding: 0; |
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} |
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.title-container { |
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display: flex; |
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flex-direction: column; |
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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: 3em; |
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text-align: center; |
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color: #333; |
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text-transform: uppercase; |
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padding: 0.5em; |
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font-weight: bold; |
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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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.gallery-container { |
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max-width: 90%; |
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margin: 20px auto; |
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text-align: center; |
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position: relative; |
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} |
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.gallery-radio { |
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display: none; |
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} |
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.gallery-image { |
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display: none; |
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width: 100%; |
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margin: 20px auto; |
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transition: opacity 0.3s ease; |
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} |
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.gallery-image img { |
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width: 100%; |
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height: auto; |
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border-radius: 10px; |
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transition: transform 0.3s ease; |
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} |
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.gallery-image img:hover { |
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transform: scale(1.05); |
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} |
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#radio1:checked ~ #image1, |
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#radio2:checked ~ #image2, |
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#radio3:checked ~ #image3 { |
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display: block; |
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} |
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.btn { |
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display: inline-block; |
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padding: 10px 20px; |
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margin: 10px; |
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background: linear-gradient(135deg, #6e8efb, #a777e3); |
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color: white; |
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border: none; |
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border-radius: 25px; |
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cursor: pointer; |
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text-decoration: none; |
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transition: all 0.7s ease; |
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box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1); |
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text-shadow: 0 1px 1px rgba(0, 0, 0, 0.2); |
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font-weight: bold; |
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} |
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.btn:hover, .btn:focus { |
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background: linear-gradient(135deg, #5b7de2, #8561c5); |
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box-shadow: 0 5px 15px rgba(0, 0, 0, 0.2); |
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} |
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.btn:active { |
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transform: translateY(1px); |
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box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1); |
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} |
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</style> |
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<h1 class="title"> |
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<span>Anime Detailer XL LoRA</span> |
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</h1> |
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<div class="gallery-container"> |
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<input type="radio" name="gallery" id="radio1" class="gallery-radio" aria-label="Less Detail"> |
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<input type="radio" name="gallery" id="radio2" class="gallery-radio" checked aria-label="Normal"> |
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<input type="radio" name="gallery" id="radio3" class="gallery-radio" aria-label="More Detail"> |
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<label for="radio1" class="btn">Less Detail</label> |
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<label for="radio2" class="btn">Normal</label> |
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<label for="radio3" class="btn">More Detail</label> |
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<!-- Image Gallery --> |
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<div id="image1" class="gallery-image"> |
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<img src="https://cdn-uploads.huggingface.co/production/uploads/6365c8dbf31ef76df4042821/RFtKV5Q6-8pWRzUA7AjOw.png" alt="sample1" loading="lazy"> |
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</div> |
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<div id="image2" class="gallery-image"> |
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<img src="https://cdn-uploads.huggingface.co/production/uploads/6365c8dbf31ef76df4042821/8_Z2IYeTOYJAMuFyJBRwX.png" alt="sample2" loading="lazy"> |
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</div> |
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<div id="image3" class="gallery-image"> |
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<img src="https://cdn-uploads.huggingface.co/production/uploads/6365c8dbf31ef76df4042821/0CyCkmFrWjPaBNLAwKMq8.png" alt="sample3" loading="lazy"> |
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</div> |
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</div> |
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## Overview |
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**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. |
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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:** 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. |
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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 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/anime-detailer-xl-lora" |
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lora_filename = "anime-detailer-xl.safetensors" |
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lora_scale_slider = 2 # -2 for less detailed result |
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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=lora_scale_slider) |
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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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## Acknowledgements |
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Our project has been enriched by the following significant works: |
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- **[Erasing Concepts from Diffusion Models](https://github.com/rohitgandikota/erasing)** by Rohit Gandikota et al. |
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- **[LECO](https://github.com/p1atdev/LECO)** by p1atdev. |
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- **[AI Toolkit](https://github.com/ostris/ai-toolkit)** by Ostris. |
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