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@@ -53,6 +53,8 @@ Sampler: DPM++ 2M SDE
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  Scheduler: Karras
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  Resolution: 1024x1024
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  # Use Cases
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  Generating evocative, nightmarish artwork for games, films, and books
@@ -60,4 +62,46 @@ Concept art and visual brainstorming for horror-themed projects
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  Exploring surreal, uncanny aesthetics and compositions
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  Pushing creative boundaries in the horror genre through AI-augmented workflows
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- CALAMITY opens up new avenues for horror-themed image generation, providing creatives with a powerful tool for conjuring up unsettling and imaginative visuals. Experiment with different prompt combinations and settings to delve into a rich spectrum of macabre imagery.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  Scheduler: Karras
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  Resolution: 1024x1024
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+ # Style Trigger word:"Sythentic Anime"
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+
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  # Use Cases
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  Generating evocative, nightmarish artwork for games, films, and books
 
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  Exploring surreal, uncanny aesthetics and compositions
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  Pushing creative boundaries in the horror genre through AI-augmented workflows
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+ CALAMITY opens up new avenues for horror-themed image generation, providing creatives with a powerful tool for conjuring up unsettling and imaginative visuals. Experiment with different prompt combinations and settings to delve into a rich spectrum of macabre imagery.
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+
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+ # Use it with 🧨 diffusers
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+ ```python
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+ import torch
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+ from diffusers import (
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+ StableDiffusionXLPipeline,
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+ KDPM2AncestralDiscreteScheduler,
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+ AutoencoderKL
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+ )
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+
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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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+
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+ # Configure the pipeline
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+ pipe = StableDiffusionXLPipeline.from_pretrained(
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+ "dataautogpt3/CALAMITY",
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+ vae=vae,
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+ torch_dtype=torch.float16
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+ )
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+ pipe.scheduler = KDPM2AncestralDiscreteScheduler.from_config(pipe.scheduler.config)
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+ pipe.to('cuda')
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+
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+ # Define prompts and generate image
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+ prompt = "Sythentic Anime"
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+ negative_prompt = ""
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+
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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=7,
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+ num_inference_steps=50,
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+ clip_skip=2
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+ ).images[0]
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+
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+
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+ image.save("generated_image.png")
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+ ```