Version: v3.0
Input
Output
This example was created by evevalentine2017
Finished in 111.5 seconds
Setting up the model...
Processing...
Loading VAE weight: models/VAE/blessed2_fp16.safetensors
Full prompt: [Transparent background:: 5], (((masterpiece))), (((best quality))), (((extremely detailed))), illustration, 1 girl, solo, mysterious, vivid color, shiny, fantasy transparent sealed hemispherical glass dome, (pinky blonde hair), (shining red eyes), full body, barefoot, ultralong wavy hair, tranquil nature, (fireflies bokeh: 1.4), Dome, close up, Dynamic actions, (((Box composition))), lean against the chair, volumetric lighting, detailed eyes, hyper detailed, light smile, highly detailed, small details, ultra detailed, best quality, intricate, 4k, 8k, trending on artstation, good anatomy, beautiful lighting, award-winning, <lora: more_details: 0.4>, glowing, light particles,
<lora: more_details: 0.8>,, <lora:add_detail:0.1>
Full negative prompt: (more than 2 arms), (more than 2 legs), (more than 2 hands), (more than 2 feet), (worst quality:1.5), (low quality:1.5), (normal quality:1.5), lowres, bad anatomy, bad hands, normal quality, ((monochrome)), ((grayscale)), negative_hand-neg
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Decoding latents in cuda:0...
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0: 640x640 1 face, 7.7ms
Speed: 3.5ms preprocess, 7.7ms inference, 31.8ms postprocess per image at shape (1, 3, 640, 640)
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Decoding latents in cuda:0...
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0: 640x640 1 hand, 7.3ms
Speed: 2.8ms preprocess, 7.3ms inference, 1.4ms postprocess per image at shape (1, 3, 640, 640)
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0: 640x640 1 face, 7.4ms
Speed: 2.8ms preprocess, 7.4ms inference, 1.6ms postprocess per image at shape (1, 3, 640, 640)
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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.
===========================================
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0: 640x640 1 face, 7.3ms
Speed: 3.0ms preprocess, 7.3ms inference, 2.0ms postprocess per image at shape (1, 3, 640, 640)
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Decoding latents in cuda:0...
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done in 0.0s
0: 640x640 4 hands, 7.0ms
Speed: 2.8ms preprocess, 7.0ms inference, 1.5ms postprocess per image at shape (1, 3, 640, 640)
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Finished.
This example was created by evevalentine2017
Finished in 111.5 seconds
Setting up the model...
Processing...
Loading VAE weight: models/VAE/blessed2_fp16.safetensors
Full prompt: [Transparent background:: 5], (((masterpiece))), (((best quality))), (((extremely detailed))), illustration, 1 girl, solo, mysterious, vivid color, shiny, fantasy transparent sealed hemispherical glass dome, (pinky blonde hair), (shining red eyes), full body, barefoot, ultralong wavy hair, tranquil nature, (fireflies bokeh: 1.4), Dome, close up, Dynamic actions, (((Box composition))), lean against the chair, volumetric lighting, detailed eyes, hyper detailed, light smile, highly detailed, small details, ultra detailed, best quality, intricate, 4k, 8k, trending on artstation, good anatomy, beautiful lighting, award-winning, <lora: more_details: 0.4>, glowing, light particles,
<lora: more_details: 0.8>,, <lora:add_detail:0.1>
Full negative prompt: (more than 2 arms), (more than 2 legs), (more than 2 hands), (more than 2 feet), (worst quality:1.5), (low quality:1.5), (normal quality:1.5), lowres, bad anatomy, bad hands, normal quality, ((monochrome)), ((grayscale)), negative_hand-neg
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0: 640x640 1 face, 7.7ms
Speed: 3.5ms preprocess, 7.7ms inference, 31.8ms postprocess per image at shape (1, 3, 640, 640)
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Decoding latents in cuda:0...
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0: 640x640 1 hand, 7.3ms
Speed: 2.8ms preprocess, 7.3ms inference, 1.4ms postprocess per image at shape (1, 3, 640, 640)
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0: 640x640 1 face, 7.4ms
Speed: 2.8ms preprocess, 7.4ms inference, 1.6ms postprocess per image at shape (1, 3, 640, 640)
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0: 640x640 6 hands, 7.7ms
Speed: 2.9ms preprocess, 7.7ms inference, 2.1ms postprocess per image at shape (1, 3, 640, 640)
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Decoding latents in cuda:0...
done in 0.23s
Move latents to cpu...
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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 0.45s
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Decoding latents in cuda:0...
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Decoding latents in cuda:0...
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Decoding latents in cuda:0...
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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, 7.3ms
Speed: 3.0ms preprocess, 7.3ms inference, 2.0ms 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 4 hands, 7.0ms
Speed: 2.8ms preprocess, 7.0ms inference, 1.5ms postprocess per image at shape (1, 3, 640, 640)
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Decoding latents in cuda:0...
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Decoding latents in cuda:0...
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Decoding latents in cuda:0...
done in 0.41s
Move latents to cpu...
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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, 7.3ms
Speed: 2.9ms preprocess, 7.3ms inference, 1.8ms postprocess per image at shape (1, 3, 640, 640)
Couldn't find network with name more_details
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Decoding latents in cuda:0...
done in 0.41s
Move latents to cpu...
done in 0.0s
0: 640x640 3 hands, 6.9ms
Speed: 2.8ms preprocess, 6.9ms inference, 1.6ms postprocess per image at shape (1, 3, 640, 640)
Couldn't find network with name more_details
Couldn't find network with name more_details
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Decoding latents in cuda:0...
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Move latents to cpu...
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Couldn't find network with name more_details
Couldn't find network with name more_details
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Decoding latents in cuda:0...
done in 0.41s
Move latents to cpu...
done in 0.0s
Couldn't find network with name more_details
Couldn't find network with name more_details
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Decoding latents in cuda:0...
done in 0.42s
Move latents to cpu...
done in 0.0s
Finished.