Version: v1.0
Input
Output
This example was created by evevalentine2017
Finished in 302.3 seconds
Setting up the model...
Preparing inputs...
Processing...
Full prompt: beautiful goth necromancer waifu, (curvy), long hair, wavy hair, heavy goth makeup, pale skin, green magic, magic swirling, raising the dead, high quality, high detail, blushing, evil, wicked, fantasy, HDR, medieval, cartoon, bokeh, very aesthetic, masterpiece, best quality, evil smile, lens flare, sunset, anime coloring
Full negative prompt: Unrealistic AND fake, anime, pixar, ugly, bad art, imperfections, cartoony, malformed, noisy, open mouth, (blur), (guassian blur), paintings, watermark, low-quality, signature, moir pattern, downsampling, aliasing, distorted, blurry, glossy, blur, jpeg artifacts, compression artifacts, poorly drawn, low-resolution, bad, distortion, twisted, excessive, exaggerated pose, exaggerated limbs, grainy, symmetrical, duplicate, error, pattern, beginner, pixelated, fake, hyper, glitch, overexposed, high-contrast, bad-contrast text, watermark, low-quality, signature, moir pattern, downsampling, aliasing, distorted, blurry, glossy, blur, jpeg artifacts, compression artifacts, poorly drawn, low-resolution, bad, distortion, twisted, excessive, exaggerated pose, exaggerated limbs, grainy, symmetrical, duplicate, error, pattern, beginner, pixelated, fake, hyper, glitch, overexposed, high-contrast, bad-contrast
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Decoding latents in cuda:0...
done in 1.7s
Move latents to cpu...
done in 0.02s
0: 640x480 1 face, 169.4ms
Speed: 2.8ms preprocess, 169.4ms inference, 23.5ms postprocess per image at shape (1, 3, 640, 480)
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Decoding latents in cuda:0...
done in 0.55s
Move latents to cpu...
done in 0.0s
0: 640x480 1 face, 8.2ms
Speed: 2.6ms preprocess, 8.2ms inference, 1.7ms postprocess per image at shape (1, 3, 640, 480)
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Decoding latents in cuda:0...
done in 0.54s
Move latents to cpu...
done in 0.0s
0: 640x480 1 face, 9.8ms
Speed: 2.9ms preprocess, 9.8ms inference, 3.6ms postprocess per image at shape (1, 3, 640, 480)
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Decoding latents in cuda:0...
done in 0.54s
Move latents to cpu...
done in 0.0s
Finished.
This example was created by evevalentine2017
Finished in 302.3 seconds
Setting up the model...
Preparing inputs...
Processing...
Full prompt: beautiful goth necromancer waifu, (curvy), long hair, wavy hair, heavy goth makeup, pale skin, green magic, magic swirling, raising the dead, high quality, high detail, blushing, evil, wicked, fantasy, HDR, medieval, cartoon, bokeh, very aesthetic, masterpiece, best quality, evil smile, lens flare, sunset, anime coloring
Full negative prompt: Unrealistic AND fake, anime, pixar, ugly, bad art, imperfections, cartoony, malformed, noisy, open mouth, (blur), (guassian blur), paintings, watermark, low-quality, signature, moir pattern, downsampling, aliasing, distorted, blurry, glossy, blur, jpeg artifacts, compression artifacts, poorly drawn, low-resolution, bad, distortion, twisted, excessive, exaggerated pose, exaggerated limbs, grainy, symmetrical, duplicate, error, pattern, beginner, pixelated, fake, hyper, glitch, overexposed, high-contrast, bad-contrast text, watermark, low-quality, signature, moir pattern, downsampling, aliasing, distorted, blurry, glossy, blur, jpeg artifacts, compression artifacts, poorly drawn, low-resolution, bad, distortion, twisted, excessive, exaggerated pose, exaggerated limbs, grainy, symmetrical, duplicate, error, pattern, beginner, pixelated, fake, hyper, glitch, overexposed, high-contrast, bad-contrast
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Decoding latents in cuda:0...
done in 1.7s
Move latents to cpu...
done in 0.02s
0: 640x480 1 face, 169.4ms
Speed: 2.8ms preprocess, 169.4ms inference, 23.5ms postprocess per image at shape (1, 3, 640, 480)
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Decoding latents in cuda:0...
done in 0.55s
Move latents to cpu...
done in 0.0s
0: 640x480 1 face, 8.2ms
Speed: 2.6ms preprocess, 8.2ms inference, 1.7ms postprocess per image at shape (1, 3, 640, 480)
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Decoding latents in cuda:0...
done in 0.54s
Move latents to cpu...
done in 0.0s
0: 640x480 1 face, 9.8ms
Speed: 2.9ms preprocess, 9.8ms inference, 3.6ms postprocess per image at shape (1, 3, 640, 480)
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Decoding latents in cuda:0...
done in 0.54s
Move latents to cpu...
done in 0.0s
Finished.