Version: v1.1
Input
Output
This example was created by evevalentine2017
Finished in 59.2 seconds
Setting up the model...
Processing...
Loading VAE weight: models/VAE/blessed2_fp16.safetensors
Full prompt: (masterpiece, best quality), RAW photo, 1girl, mgedemon, full body shot, thighhighs, high heels, boots, elbow glove, wings, tail, black sclera, intricate skin, obsidian black, blood red fox eyes, Two large horns grow on the top of her head, two small ones on the sides of her face, long tresses ebony hair back, high cheekbones, perfectly sculpted features, two wings, wide wings of a predatory bird, large bust and hips, small waist, volumetric light, glossy skin, shiny metal, <lora:FaceBeauty_qinglong_V3:1>, <lora:mgedemon-000005:0.7>, <lora:add_detail:-0.1>, <lora:add_brightness:0.4>, <lora:contrast_slider_v10:-1.15>, <lora:add_saturation:-0.47>
Full negative prompt: nsfw, nipples, topless, low quality, lowres, worst quality, normal quality, earth, land, oversized hairstyle, bad-image-v2-39000, By bad artist -neg, verybadimagenegative_v1.3
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Decoding latents in cuda:0...
===========================================
A tensor with all NaNs was produced in VAE.
Converted VAE into 32-bit float and retry.
===========================================
done in 1.58s
Move latents to cpu...
done in 0.02s
0: 640x640 1 face, 7.7ms
Speed: 3.5ms preprocess, 7.7ms inference, 31.3ms postprocess per image at shape (1, 3, 640, 640)
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Decoding latents in cuda:0...
done in 0.41s
Move latents to cpu...
done in 0.0s
0: 640x640 1 face, 7.2ms
Speed: 2.7ms preprocess, 7.2ms inference, 1.3ms postprocess per image at shape (1, 3, 640, 640)
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Decoding latents in cuda:0...
done in 0.42s
Move latents to cpu...
done in 0.0s
0: 640x640 1 face, 7.3ms
Speed: 2.7ms preprocess, 7.3ms inference, 1.5ms postprocess per image at shape (1, 3, 640, 640)
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Decoding latents in cuda:0...
done in 0.42s
Move latents to cpu...
done in 0.0s
0: 640x640 1 face, 7.2ms
Speed: 2.8ms preprocess, 7.2ms inference, 1.6ms postprocess per image at shape (1, 3, 640, 640)
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Decoding latents in cuda:0...
done in 0.41s
Move latents to cpu...
done in 0.0s
Uploading outputs...
Finished.
This example was created by evevalentine2017
Finished in 59.2 seconds
Setting up the model...
Processing...
Loading VAE weight: models/VAE/blessed2_fp16.safetensors
Full prompt: (masterpiece, best quality), RAW photo, 1girl, mgedemon, full body shot, thighhighs, high heels, boots, elbow glove, wings, tail, black sclera, intricate skin, obsidian black, blood red fox eyes, Two large horns grow on the top of her head, two small ones on the sides of her face, long tresses ebony hair back, high cheekbones, perfectly sculpted features, two wings, wide wings of a predatory bird, large bust and hips, small waist, volumetric light, glossy skin, shiny metal, <lora:FaceBeauty_qinglong_V3:1>, <lora:mgedemon-000005:0.7>, <lora:add_detail:-0.1>, <lora:add_brightness:0.4>, <lora:contrast_slider_v10:-1.15>, <lora:add_saturation:-0.47>
Full negative prompt: nsfw, nipples, topless, low quality, lowres, worst quality, normal quality, earth, land, oversized hairstyle, bad-image-v2-39000, By bad artist -neg, verybadimagenegative_v1.3
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Decoding latents in cuda:0...
===========================================
A tensor with all NaNs was produced in VAE.
Converted VAE into 32-bit float and retry.
===========================================
done in 1.58s
Move latents to cpu...
done in 0.02s
0: 640x640 1 face, 7.7ms
Speed: 3.5ms preprocess, 7.7ms inference, 31.3ms postprocess per image at shape (1, 3, 640, 640)
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Decoding latents in cuda:0...
done in 0.41s
Move latents to cpu...
done in 0.0s
0: 640x640 1 face, 7.2ms
Speed: 2.7ms preprocess, 7.2ms inference, 1.3ms postprocess per image at shape (1, 3, 640, 640)
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Decoding latents in cuda:0...
done in 0.42s
Move latents to cpu...
done in 0.0s
0: 640x640 1 face, 7.3ms
Speed: 2.7ms preprocess, 7.3ms inference, 1.5ms postprocess per image at shape (1, 3, 640, 640)
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Decoding latents in cuda:0...
done in 0.42s
Move latents to cpu...
done in 0.0s
0: 640x640 1 face, 7.2ms
Speed: 2.8ms preprocess, 7.2ms inference, 1.6ms postprocess per image at shape (1, 3, 640, 640)
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Decoding latents in cuda:0...
done in 0.41s
Move latents to cpu...
done in 0.0s
Uploading outputs...
Finished.