alexgenovese/sdxl-custom-model 🔢📝 → 🖼️

Starting fp16 torch.float32 cuda
Fused all loras in UNet
Applied correction to prompts positive a full body realistic photo of beautiful woman 40 y.o, walking in Madison Square Garden, smile, blue eyes, short hair, dark makeup, hyperdetailed photography, soft light, (full body)1.21, (3/4 view)1.21, detailed eyes, (masterpiece,best quality,ultra_detailed,highres,absurdres)1.20, 4k, professional, intricate details even to the smallest particle, extreme detail of the environment, sharp portrait, well lit, (ultra realistic, realistic)1.90, beautiful shadows, bright, photo quality, masterpiece, 8k, ultra-detailed, highly detailed, sharp focus, award winning, octane render unreal engine, volumetrics dtx, high definition, bokeh, (fashion model)1.50, (realistic, photorealistic)2.00, (fashion-forward)1.30
Applied correction to negative prompts  ,(worst quality, low quality, normal quality, lowres, low details, oversaturated, undersaturated, overexposed, underexposed, grayscale, bw, bad photo, bad photography, bad art)1.40, (watermark, signature, text font, username, error, logo, words, letters, digits, autograph, trademark, name)1.20, (blur, blurry, grainy)1.10, morbid, ugly, asymmetrical, mutated malformed, mutilated, poorly lit, bad shadow, draft, cropped, out of frame, cut off, censored, jpeg artifacts, out of focus, glitch, duplicate, (airbrushed, cartoon, anime, semi-realistic, cgi, render, blender, digital art, manga, amateur)1.30, (3D ,3D Game, 3D Game Scene, 3D Character)1.10, (bad hands, bad anatomy, bad body, bad face, bad teeth, bad arms, bad legs, deformities)1.30, peopleneg, unaestheticXL_Jug6
Applied optimization
Created compel for prompts
Starting inference...
timestep: 946 max: 3.99 min: -4.34 mean: -0.01
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timestep: 919 max: 4.03 min: -4.43 mean: 0.0
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timestep: 892 max: 4.04 min: -4.39 mean: -0.01
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timestep: 865 max: 4.05 min: -4.46 mean: -0.01
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timestep: 838 max: 4.04 min: -4.48 mean: -0.02
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timestep: 811 max: 4.04 min: -4.51 mean: -0.02
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timestep: 784 max: 4.04 min: -4.53 mean: -0.02
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timestep: 757 max: 4.03 min: -4.55mean: -0.02
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timestep: 730 max: 4.03 min: -4.56 mean: -0.03
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timestep: 703 max: 4.0 min: -4.55 mean: -0.03
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timestep: 676 max: 3.97 min: -4.54 mean: -0.03
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timestep: 649 max: 3.96 min: -4.54 mean: -0.03
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timestep: 622 max: 3.94 min: -4.53 mean: -0.03
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timestep: 595 max: 3.91 min: -4.51 mean: -0.03
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timestep: 568 max: 3.88 min: -4.5 mean: -0.03
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timestep: 541 max: 3.84 min: -4.48 mean: -0.03
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timestep: 514 max: 3.8 min: -4.45 mean: -0.03
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timestep: 487 max: 3.75 min: -4.42 mean: -0.03
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timestep: 460 max: 3.7 min: -4.37 mean: -0.03
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timestep: 433 max: 3.64 min: -4.32 mean: -0.03
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timestep: 406 max: 3.57 min: -4.27 mean: -0.03
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timestep: 379 max: 3.5 min: -4.2 mean: -0.03
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timestep: 352 max: 3.43 min: -4.13 mean: -0.03
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timestep: 325 max: 3.36 min: -4.05 mean: -0.03
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timestep: 298 max: 3.3 min: -3.96 mean: -0.03
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timestep: 271 max: 3.29 min: -3.87 mean: -0.03
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timestep: 244 max: 3.27 min: -3.8mean: -0.02
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timestep: 217 max: 3.26 min: -3.74 mean: -0.02
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timestep: 197 max: 3.13 min: -3.54 mean: -0.02
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timestep: 169 max: 3.01 min: -3.35 mean: -0.02
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timestep: 141 max: 2.9 min: -3.17 mean: -0.02
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timestep: 113 max: 2.8 min: -2.98 mean: -0.02
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timestep: 85 max: 2.7 min: -2.79 mean: -0.03
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timestep: 57 max: 2.58 min: -2.58 mean: -0.03
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timestep: 29 max: 2.4 min: -2.42 mean: -0.03
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timestep: 1 max: 2.45 min: -2.42 mean: -0.03
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100%|██████████| 8/8 [00:05<00:00,  1.59it/s]
Inference took:  31.832138061523438 34902