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Cute Girl Portrait with AW Painting
aw-painting:v1.2
evevalentine2017
evevalentine2017
·
12/17/2023
345
Input
prompt
Specify things to see in the output
portrait of a girl, silver hair, blue eyes, dynamic expression, blue lipstick, black dress, bare shoulders, floral background, colors, glitters, hyper realistic, cinematic, vivid lighting, (highres, highly detailed:1.1), aesthetic, masterpiece,
negative_prompt
Specify things to not see in the output
ng_deepnegative_v1_75t, (bad-hands-5:1.2), (worst quality:2), (low quality:2), (normal quality:2), lowres, bad anatomy, bad hands, ((monochrome)), ((grayscale)) watermark, moles, large breast, big breast
num_outputs
Number of output images
4
width
Output image width
768
height
Output image height
768
enhance_face_with_adetailer
Enhance face with adetailer
true
enhance_hands_with_adetailer
Enhance hands with adetailer
false
adetailer_denoising_strength
1: completely redraw face or hands / 0: no effect on output images
0.55
detail
Enhance/diminish detail while keeping the overall style/character
0
brightness
Adjust brightness
0
contrast
Adjust contrast
0
saturation
Adjust saturation
0
seed
Same seed with the same prompt generates the same image. Set as -1 to randomize output.
1256557220
input_image
Base image that the output should be generated from. This is useful when you want to add some detail to input_image. For example, if prompt is "sunglasses" and input_image has a man, there is the man wearing sunglasses in the output.
input_image_redrawing_strength
How differ the output is from input_image. Used only when input_image is given.
0.55
reference_image
Image with which the output should share identity (e.g. face of a person or type of a dog)
reference_image_strength
Strength of applying reference_image. Used only when reference_image is given.
1
reference_pose_image
Image with a reference pose
reference_pose_strength
Strength of applying reference_pose_image. Used only when reference_pose_image is given.
1
reference_depth_image
Image with a reference depth
reference_depth_strength
Strength of applying reference_depth_image. Used only when reference_depth_image is given.
1
sampler
Sampler type
DPM++ 2M Karras
samping_steps
Number of denoising steps
40
cfg_scale
Scale for classifier-free guidance
7
clip_skip
The number of last layers of CLIP network to skip
2
vae
Select VAE
blessed2_fp16.safetensors
lora_1
LoRA file. Apply by writing the following in prompt: <lora:FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE>
lora_2
LoRA file. Apply by writing the following in prompt: <lora:FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE>
lora_3
LoRA file. Apply by writing the following in prompt: <lora:FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE>
embedding_1
Embedding file (textural inversion). Apply by writing the following in prompt or negative prompt: (FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE)
bad-hands-5.pt
embedding_2
Embedding file (textural inversion). Apply by writing the following in prompt or negative prompt: (FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE)
ng_deepnegative_v1_75t.pt
embedding_3
Embedding file (textural inversion). Apply by writing the following in prompt or negative prompt: (FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE)
disable_prompt_modification
Disable automatically adding suggested prompt modification. Built-in LoRAs and trigger words will remain.
false
Output
https://files.tungsten.run/uploads/d164874f2e764661a727c07e4367cf00/00000-1256557220.webp
https://files.tungsten.run/uploads/ccb03a461c83457ea9e6808efda527c5/00001-1256557221.webp
https://files.tungsten.run/uploads/08191421c42940219ae5a2276b998fa5/00002-1256557222.webp
https://files.tungsten.run/uploads/eb478e6beddf4f6db67b73f909c03c76/00003-1256557223.webp
Finished in 49.2 seconds
Preparing inputs... Processing... Loading VAE weight: models/VAE/blessed2_fp16.safetensors Full prompt: portrait of a girl, silver hair, blue eyes, dynamic expression, blue lipstick, black dress, bare shoulders, floral background, colors, glitters, hyper realistic, cinematic, vivid lighting, (highres, highly detailed:1.1), aesthetic, masterpiece, Full negative prompt: ng_deepnegative_v1_75t, (bad-hands-5:1.2), (worst quality:2), (low quality:2), (normal quality:2), lowres, bad anatomy, bad hands, ((monochrome)), ((grayscale)) watermark, moles, large breast, big breast 0%| | 0/40 [00:00<?, ?it/s] 2%|▎ | 1/40 [00:00<00:25, 1.56it/s] 5%|▌ | 2/40 [00:01<00:24, 1.52it/s] 8%|▊ | 3/40 [00:01<00:24, 1.53it/s] 10%|█ | 4/40 [00:02<00:23, 1.52it/s] 12%|█▎ | 5/40 [00:03<00:23, 1.51it/s] 15%|█▌ | 6/40 [00:03<00:22, 1.52it/s] 18%|█▊ | 7/40 [00:04<00:21, 1.51it/s] 20%|██ | 8/40 [00:05<00:21, 1.51it/s] 22%|██▎ | 9/40 [00:05<00:20, 1.51it/s] 25%|██▌ | 10/40 [00:06<00:19, 1.51it/s] 28%|██▊ | 11/40 [00:07<00:19, 1.51it/s] 30%|███ | 12/40 [00:07<00:18, 1.51it/s] 32%|███▎ | 13/40 [00:08<00:17, 1.50it/s] 35%|███▌ | 14/40 [00:09<00:17, 1.50it/s] 38%|███▊ | 15/40 [00:09<00:16, 1.50it/s] 40%|████ | 16/40 [00:10<00:16, 1.50it/s] 42%|████▎ | 17/40 [00:11<00:15, 1.50it/s] 45%|████▌ | 18/40 [00:11<00:14, 1.50it/s] 48%|████▊ | 19/40 [00:12<00:14, 1.50it/s] 50%|█████ | 20/40 [00:13<00:13, 1.49it/s] 52%|█████▎ | 21/40 [00:13<00:12, 1.49it/s] 55%|█████▌ | 22/40 [00:14<00:12, 1.49it/s] 57%|█████▊ | 23/40 [00:15<00:11, 1.48it/s] 60%|██████ | 24/40 [00:15<00:10, 1.49it/s] 62%|██████▎ | 25/40 [00:16<00:10, 1.49it/s] 65%|██████▌ | 26/40 [00:17<00:09, 1.48it/s] 68%|██████▊ | 27/40 [00:18<00:08, 1.48it/s] 70%|███████ | 28/40 [00:18<00:08, 1.48it/s] 72%|███████▎ | 29/40 [00:19<00:07, 1.48it/s] 75%|███████▌ | 30/40 [00:20<00:06, 1.48it/s] 78%|███████▊ | 31/40 [00:20<00:06, 1.48it/s] 80%|████████ | 32/40 [00:21<00:05, 1.48it/s] 82%|████████▎ | 33/40 [00:22<00:04, 1.47it/s] 85%|████████▌ | 34/40 [00:22<00:04, 1.47it/s] 88%|████████▊ | 35/40 [00:23<00:03, 1.47it/s] 90%|█████████ | 36/40 [00:24<00:02, 1.47it/s] 92%|█████████▎| 37/40 [00:24<00:02, 1.47it/s] 95%|█████████▌| 38/40 [00:25<00:01, 1.47it/s] 98%|█████████▊| 39/40 [00:26<00:00, 1.47it/s] 100%|██████████| 40/40 [00:26<00:00, 1.47it/s] 100%|██████████| 40/40 [00:26<00:00, 1.49it/s] Decoding latents in cuda:0... =========================================== A tensor with all NaNs was produced in VAE. Converted VAE into 32-bit float and retry. =========================================== done in 1.76s Move latents to cpu... done in 0.01s 0%| | 0/23 [00:00<?, ?it/s] 4%|▍ | 1/23 [00:00<00:03, 6.80it/s] 9%|▊ | 2/23 [00:00<00:03, 6.57it/s] 13%|█▎ | 3/23 [00:00<00:03, 6.49it/s] 17%|█▋ | 4/23 [00:00<00:02, 6.45it/s] 22%|██▏ | 5/23 [00:00<00:02, 6.45it/s] 26%|██▌ | 6/23 [00:00<00:02, 6.34it/s] 30%|███ | 7/23 [00:01<00:02, 6.24it/s] 35%|███▍ | 8/23 [00:01<00:02, 6.25it/s] 39%|███▉ | 9/23 [00:01<00:02, 6.27it/s] 43%|████▎ | 10/23 [00:01<00:02, 6.31it/s] 48%|████▊ | 11/23 [00:01<00:01, 6.35it/s] 52%|█████▏ | 12/23 [00:01<00:01, 6.35it/s] 57%|█████▋ | 13/23 [00:02<00:01, 6.32it/s] 61%|██████ | 14/23 [00:02<00:01, 6.30it/s] 65%|██████▌ | 15/23 [00:02<00:01, 6.31it/s] 70%|██████▉ | 16/23 [00:02<00:01, 6.34it/s] 74%|███████▍ | 17/23 [00:02<00:00, 6.34it/s] 78%|███████▊ | 18/23 [00:02<00:00, 6.31it/s] 83%|████████▎ | 19/23 [00:02<00:00, 6.27it/s] 87%|████████▋ | 20/23 [00:03<00:00, 6.26it/s] 91%|█████████▏| 21/23 [00:03<00:00, 6.26it/s] 96%|█████████▌| 22/23 [00:03<00:00, 6.27it/s] 100%|██████████| 23/23 [00:03<00:00, 6.30it/s] 100%|██████████| 23/23 [00:03<00:00, 6.33it/s] Decoding latents in cuda:0... done in 0.42s Move latents to cpu... done in 0.0s 0%| | 0/23 [00:00<?, ?it/s] 4%|▍ | 1/23 [00:00<00:03, 6.63it/s] 9%|▊ | 2/23 [00:00<00:03, 6.44it/s] 13%|█▎ | 3/23 [00:00<00:03, 6.41it/s] 17%|█▋ | 4/23 [00:00<00:02, 6.44it/s] 22%|██▏ | 5/23 [00:00<00:02, 6.43it/s] 26%|██▌ | 6/23 [00:00<00:02, 6.35it/s] 30%|███ | 7/23 [00:01<00:02, 6.28it/s] 35%|███▍ | 8/23 [00:01<00:02, 6.29it/s] 39%|███▉ | 9/23 [00:01<00:02, 6.31it/s] 43%|████▎ | 10/23 [00:01<00:02, 6.35it/s] 48%|████▊ | 11/23 [00:01<00:01, 6.37it/s] 52%|█████▏ | 12/23 [00:01<00:01, 6.33it/s] 57%|█████▋ | 13/23 [00:02<00:01, 6.28it/s] 61%|██████ | 14/23 [00:02<00:01, 6.29it/s] 65%|██████▌ | 15/23 [00:02<00:01, 6.29it/s] 70%|██████▉ | 16/23 [00:02<00:01, 6.32it/s] 74%|███████▍ | 17/23 [00:02<00:00, 6.33it/s] 78%|███████▊ | 18/23 [00:02<00:00, 6.34it/s] 83%|████████▎ | 19/23 [00:02<00:00, 6.32it/s] 87%|████████▋ | 20/23 [00:03<00:00, 6.31it/s] 91%|█████████▏| 21/23 [00:03<00:00, 6.30it/s] 96%|█████████▌| 22/23 [00:03<00:00, 6.33it/s] 100%|██████████| 23/23 [00:03<00:00, 6.35it/s] 100%|██████████| 23/23 [00:03<00:00, 6.34it/s] Decoding latents in cuda:0... done in 0.41s Move latents to cpu... done in 0.0s 0%| | 0/23 [00:00<?, ?it/s] 4%|▍ | 1/23 [00:00<00:03, 6.80it/s] 9%|▊ | 2/23 [00:00<00:03, 6.58it/s] 13%|█▎ | 3/23 [00:00<00:03, 6.51it/s] 17%|█▋ | 4/23 [00:00<00:02, 6.49it/s] 22%|██▏ | 5/23 [00:00<00:02, 6.48it/s] 26%|██▌ | 6/23 [00:00<00:02, 6.39it/s] 30%|███ | 7/23 [00:01<00:02, 6.32it/s] 35%|███▍ | 8/23 [00:01<00:02, 6.20it/s] 39%|███▉ | 9/23 [00:01<00:02, 6.28it/s] 43%|████▎ | 10/23 [00:01<00:02, 6.35it/s] 48%|████▊ | 11/23 [00:01<00:01, 6.38it/s] 52%|█████▏ | 12/23 [00:01<00:01, 6.35it/s] 57%|█████▋ | 13/23 [00:02<00:01, 6.28it/s] 61%|██████ | 14/23 [00:02<00:01, 6.25it/s] 65%|██████▌ | 15/23 [00:02<00:01, 6.30it/s] 70%|██████▉ | 16/23 [00:02<00:01, 6.33it/s] 74%|███████▍ | 17/23 [00:02<00:00, 6.36it/s] 78%|███████▊ | 18/23 [00:02<00:00, 6.34it/s] 83%|████████▎ | 19/23 [00:02<00:00, 6.30it/s] 87%|████████▋ | 20/23 [00:03<00:00, 6.30it/s] 91%|█████████▏| 21/23 [00:03<00:00, 6.11it/s] 96%|█████████▌| 22/23 [00:03<00:00, 6.20it/s] 100%|██████████| 23/23 [00:03<00:00, 6.24it/s] 100%|██████████| 23/23 [00:03<00:00, 6.32it/s] Decoding latents in cuda:0... done in 0.41s Move latents to cpu... done in 0.0s 0%| | 0/23 [00:00<?, ?it/s] 4%|▍ | 1/23 [00:00<00:03, 6.76it/s] 9%|▊ | 2/23 [00:00<00:03, 6.56it/s] 13%|█▎ | 3/23 [00:00<00:03, 6.52it/s] 17%|█▋ | 4/23 [00:00<00:02, 6.50it/s] 22%|██▏ | 5/23 [00:00<00:02, 6.47it/s] 26%|██▌ | 6/23 [00:00<00:02, 6.37it/s] 30%|███ | 7/23 [00:01<00:02, 6.30it/s] 35%|███▍ | 8/23 [00:01<00:02, 6.32it/s] 39%|███▉ | 9/23 [00:01<00:02, 6.36it/s] 43%|████▎ | 10/23 [00:01<00:02, 6.30it/s] 48%|████▊ | 11/23 [00:01<00:01, 6.33it/s] 52%|█████▏ | 12/23 [00:01<00:01, 6.34it/s] 57%|█████▋ | 13/23 [00:02<00:01, 6.29it/s] 61%|██████ | 14/23 [00:02<00:01, 6.30it/s] 65%|██████▌ | 15/23 [00:02<00:01, 6.33it/s] 70%|██████▉ | 16/23 [00:02<00:01, 6.36it/s] 74%|███████▍ | 17/23 [00:02<00:00, 6.39it/s] 78%|███████▊ | 18/23 [00:02<00:00, 6.38it/s] 83%|████████▎ | 19/23 [00:02<00:00, 6.32it/s] 87%|████████▋ | 20/23 [00:03<00:00, 6.31it/s] 91%|█████████▏| 21/23 [00:03<00:00, 6.33it/s] 96%|█████████▌| 22/23 [00:03<00:00, 6.36it/s] 100%|██████████| 23/23 [00:03<00:00, 6.39it/s] 100%|██████████| 23/23 [00:03<00:00, 6.37it/s] Decoding latents in cuda:0... done in 0.41s Move latents to cpu... done in 0.0s Finished.
prompt
Specify things to see in the output
portrait of a girl, silver hair, blue eyes, dynamic expression, blue lipstick, black dress, bare shoulders, floral background, colors, glitters, hyper realistic, cinematic, vivid lighting, (highres, highly detailed:1.1), aesthetic, masterpiece,
negative_prompt
Specify things to not see in the output
ng_deepnegative_v1_75t, (bad-hands-5:1.2), (worst quality:2), (low quality:2), (normal quality:2), lowres, bad anatomy, bad hands, ((monochrome)), ((grayscale)) watermark, moles, large breast, big breast
num_outputs
Number of output images
4
width
Output image width
768
height
Output image height
768
enhance_face_with_adetailer
Enhance face with adetailer
true
enhance_hands_with_adetailer
Enhance hands with adetailer
false
adetailer_denoising_strength
1: completely redraw face or hands / 0: no effect on output images
0.55
detail
Enhance/diminish detail while keeping the overall style/character
0
brightness
Adjust brightness
0
contrast
Adjust contrast
0
saturation
Adjust saturation
0
seed
Same seed with the same prompt generates the same image. Set as -1 to randomize output.
1256557220
input_image
Base image that the output should be generated from. This is useful when you want to add some detail to input_image. For example, if prompt is "sunglasses" and input_image has a man, there is the man wearing sunglasses in the output.
input_image_redrawing_strength
How differ the output is from input_image. Used only when input_image is given.
0.55
reference_image
Image with which the output should share identity (e.g. face of a person or type of a dog)
reference_image_strength
Strength of applying reference_image. Used only when reference_image is given.
1
reference_pose_image
Image with a reference pose
reference_pose_strength
Strength of applying reference_pose_image. Used only when reference_pose_image is given.
1
reference_depth_image
Image with a reference depth
reference_depth_strength
Strength of applying reference_depth_image. Used only when reference_depth_image is given.
1
sampler
Sampler type
DPM++ 2M Karras
samping_steps
Number of denoising steps
40
cfg_scale
Scale for classifier-free guidance
7
clip_skip
The number of last layers of CLIP network to skip
2
vae
Select VAE
blessed2_fp16.safetensors
lora_1
LoRA file. Apply by writing the following in prompt: <lora:FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE>
lora_2
LoRA file. Apply by writing the following in prompt: <lora:FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE>
lora_3
LoRA file. Apply by writing the following in prompt: <lora:FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE>
embedding_1
Embedding file (textural inversion). Apply by writing the following in prompt or negative prompt: (FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE)
bad-hands-5.pt
embedding_2
Embedding file (textural inversion). Apply by writing the following in prompt or negative prompt: (FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE)
ng_deepnegative_v1_75t.pt
embedding_3
Embedding file (textural inversion). Apply by writing the following in prompt or negative prompt: (FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE)
disable_prompt_modification
Disable automatically adding suggested prompt modification. Built-in LoRAs and trigger words will remain.
false
https://files.tungsten.run/uploads/d164874f2e764661a727c07e4367cf00/00000-1256557220.webp
https://files.tungsten.run/uploads/ccb03a461c83457ea9e6808efda527c5/00001-1256557221.webp
https://files.tungsten.run/uploads/08191421c42940219ae5a2276b998fa5/00002-1256557222.webp
https://files.tungsten.run/uploads/eb478e6beddf4f6db67b73f909c03c76/00003-1256557223.webp
Finished in 49.2 seconds
Preparing inputs... Processing... Loading VAE weight: models/VAE/blessed2_fp16.safetensors Full prompt: portrait of a girl, silver hair, blue eyes, dynamic expression, blue lipstick, black dress, bare shoulders, floral background, colors, glitters, hyper realistic, cinematic, vivid lighting, (highres, highly detailed:1.1), aesthetic, masterpiece, Full negative prompt: ng_deepnegative_v1_75t, (bad-hands-5:1.2), (worst quality:2), (low quality:2), (normal quality:2), lowres, bad anatomy, bad hands, ((monochrome)), ((grayscale)) watermark, moles, large breast, big breast 0%| | 0/40 [00:00<?, ?it/s] 2%|▎ | 1/40 [00:00<00:25, 1.56it/s] 5%|▌ | 2/40 [00:01<00:24, 1.52it/s] 8%|▊ | 3/40 [00:01<00:24, 1.53it/s] 10%|█ | 4/40 [00:02<00:23, 1.52it/s] 12%|█▎ | 5/40 [00:03<00:23, 1.51it/s] 15%|█▌ | 6/40 [00:03<00:22, 1.52it/s] 18%|█▊ | 7/40 [00:04<00:21, 1.51it/s] 20%|██ | 8/40 [00:05<00:21, 1.51it/s] 22%|██▎ | 9/40 [00:05<00:20, 1.51it/s] 25%|██▌ | 10/40 [00:06<00:19, 1.51it/s] 28%|██▊ | 11/40 [00:07<00:19, 1.51it/s] 30%|███ | 12/40 [00:07<00:18, 1.51it/s] 32%|███▎ | 13/40 [00:08<00:17, 1.50it/s] 35%|███▌ | 14/40 [00:09<00:17, 1.50it/s] 38%|███▊ | 15/40 [00:09<00:16, 1.50it/s] 40%|████ | 16/40 [00:10<00:16, 1.50it/s] 42%|████▎ | 17/40 [00:11<00:15, 1.50it/s] 45%|████▌ | 18/40 [00:11<00:14, 1.50it/s] 48%|████▊ | 19/40 [00:12<00:14, 1.50it/s] 50%|█████ | 20/40 [00:13<00:13, 1.49it/s] 52%|█████▎ | 21/40 [00:13<00:12, 1.49it/s] 55%|█████▌ | 22/40 [00:14<00:12, 1.49it/s] 57%|█████▊ | 23/40 [00:15<00:11, 1.48it/s] 60%|██████ | 24/40 [00:15<00:10, 1.49it/s] 62%|██████▎ | 25/40 [00:16<00:10, 1.49it/s] 65%|██████▌ | 26/40 [00:17<00:09, 1.48it/s] 68%|██████▊ | 27/40 [00:18<00:08, 1.48it/s] 70%|███████ | 28/40 [00:18<00:08, 1.48it/s] 72%|███████▎ | 29/40 [00:19<00:07, 1.48it/s] 75%|███████▌ | 30/40 [00:20<00:06, 1.48it/s] 78%|███████▊ | 31/40 [00:20<00:06, 1.48it/s] 80%|████████ | 32/40 [00:21<00:05, 1.48it/s] 82%|████████▎ | 33/40 [00:22<00:04, 1.47it/s] 85%|████████▌ | 34/40 [00:22<00:04, 1.47it/s] 88%|████████▊ | 35/40 [00:23<00:03, 1.47it/s] 90%|█████████ | 36/40 [00:24<00:02, 1.47it/s] 92%|█████████▎| 37/40 [00:24<00:02, 1.47it/s] 95%|█████████▌| 38/40 [00:25<00:01, 1.47it/s] 98%|█████████▊| 39/40 [00:26<00:00, 1.47it/s] 100%|██████████| 40/40 [00:26<00:00, 1.47it/s] 100%|██████████| 40/40 [00:26<00:00, 1.49it/s] Decoding latents in cuda:0... =========================================== A tensor with all NaNs was produced in VAE. Converted VAE into 32-bit float and retry. =========================================== done in 1.76s Move latents to cpu... done in 0.01s 0%| | 0/23 [00:00<?, ?it/s] 4%|▍ | 1/23 [00:00<00:03, 6.80it/s] 9%|▊ | 2/23 [00:00<00:03, 6.57it/s] 13%|█▎ | 3/23 [00:00<00:03, 6.49it/s] 17%|█▋ | 4/23 [00:00<00:02, 6.45it/s] 22%|██▏ | 5/23 [00:00<00:02, 6.45it/s] 26%|██▌ | 6/23 [00:00<00:02, 6.34it/s] 30%|███ | 7/23 [00:01<00:02, 6.24it/s] 35%|███▍ | 8/23 [00:01<00:02, 6.25it/s] 39%|███▉ | 9/23 [00:01<00:02, 6.27it/s] 43%|████▎ | 10/23 [00:01<00:02, 6.31it/s] 48%|████▊ | 11/23 [00:01<00:01, 6.35it/s] 52%|█████▏ | 12/23 [00:01<00:01, 6.35it/s] 57%|█████▋ | 13/23 [00:02<00:01, 6.32it/s] 61%|██████ | 14/23 [00:02<00:01, 6.30it/s] 65%|██████▌ | 15/23 [00:02<00:01, 6.31it/s] 70%|██████▉ | 16/23 [00:02<00:01, 6.34it/s] 74%|███████▍ | 17/23 [00:02<00:00, 6.34it/s] 78%|███████▊ | 18/23 [00:02<00:00, 6.31it/s] 83%|████████▎ | 19/23 [00:02<00:00, 6.27it/s] 87%|████████▋ | 20/23 [00:03<00:00, 6.26it/s] 91%|█████████▏| 21/23 [00:03<00:00, 6.26it/s] 96%|█████████▌| 22/23 [00:03<00:00, 6.27it/s] 100%|██████████| 23/23 [00:03<00:00, 6.30it/s] 100%|██████████| 23/23 [00:03<00:00, 6.33it/s] Decoding latents in cuda:0... done in 0.42s Move latents to cpu... done in 0.0s 0%| | 0/23 [00:00<?, ?it/s] 4%|▍ | 1/23 [00:00<00:03, 6.63it/s] 9%|▊ | 2/23 [00:00<00:03, 6.44it/s] 13%|█▎ | 3/23 [00:00<00:03, 6.41it/s] 17%|█▋ | 4/23 [00:00<00:02, 6.44it/s] 22%|██▏ | 5/23 [00:00<00:02, 6.43it/s] 26%|██▌ | 6/23 [00:00<00:02, 6.35it/s] 30%|███ | 7/23 [00:01<00:02, 6.28it/s] 35%|███▍ | 8/23 [00:01<00:02, 6.29it/s] 39%|███▉ | 9/23 [00:01<00:02, 6.31it/s] 43%|████▎ | 10/23 [00:01<00:02, 6.35it/s] 48%|████▊ | 11/23 [00:01<00:01, 6.37it/s] 52%|█████▏ | 12/23 [00:01<00:01, 6.33it/s] 57%|█████▋ | 13/23 [00:02<00:01, 6.28it/s] 61%|██████ | 14/23 [00:02<00:01, 6.29it/s] 65%|██████▌ | 15/23 [00:02<00:01, 6.29it/s] 70%|██████▉ | 16/23 [00:02<00:01, 6.32it/s] 74%|███████▍ | 17/23 [00:02<00:00, 6.33it/s] 78%|███████▊ | 18/23 [00:02<00:00, 6.34it/s] 83%|████████▎ | 19/23 [00:02<00:00, 6.32it/s] 87%|████████▋ | 20/23 [00:03<00:00, 6.31it/s] 91%|█████████▏| 21/23 [00:03<00:00, 6.30it/s] 96%|█████████▌| 22/23 [00:03<00:00, 6.33it/s] 100%|██████████| 23/23 [00:03<00:00, 6.35it/s] 100%|██████████| 23/23 [00:03<00:00, 6.34it/s] Decoding latents in cuda:0... done in 0.41s Move latents to cpu... done in 0.0s 0%| | 0/23 [00:00<?, ?it/s] 4%|▍ | 1/23 [00:00<00:03, 6.80it/s] 9%|▊ | 2/23 [00:00<00:03, 6.58it/s] 13%|█▎ | 3/23 [00:00<00:03, 6.51it/s] 17%|█▋ | 4/23 [00:00<00:02, 6.49it/s] 22%|██▏ | 5/23 [00:00<00:02, 6.48it/s] 26%|██▌ | 6/23 [00:00<00:02, 6.39it/s] 30%|███ | 7/23 [00:01<00:02, 6.32it/s] 35%|███▍ | 8/23 [00:01<00:02, 6.20it/s] 39%|███▉ | 9/23 [00:01<00:02, 6.28it/s] 43%|████▎ | 10/23 [00:01<00:02, 6.35it/s] 48%|████▊ | 11/23 [00:01<00:01, 6.38it/s] 52%|█████▏ | 12/23 [00:01<00:01, 6.35it/s] 57%|█████▋ | 13/23 [00:02<00:01, 6.28it/s] 61%|██████ | 14/23 [00:02<00:01, 6.25it/s] 65%|██████▌ | 15/23 [00:02<00:01, 6.30it/s] 70%|██████▉ | 16/23 [00:02<00:01, 6.33it/s] 74%|███████▍ | 17/23 [00:02<00:00, 6.36it/s] 78%|███████▊ | 18/23 [00:02<00:00, 6.34it/s] 83%|████████▎ | 19/23 [00:02<00:00, 6.30it/s] 87%|████████▋ | 20/23 [00:03<00:00, 6.30it/s] 91%|█████████▏| 21/23 [00:03<00:00, 6.11it/s] 96%|█████████▌| 22/23 [00:03<00:00, 6.20it/s] 100%|██████████| 23/23 [00:03<00:00, 6.24it/s] 100%|██████████| 23/23 [00:03<00:00, 6.32it/s] Decoding latents in cuda:0... done in 0.41s Move latents to cpu... done in 0.0s 0%| | 0/23 [00:00<?, ?it/s] 4%|▍ | 1/23 [00:00<00:03, 6.76it/s] 9%|▊ | 2/23 [00:00<00:03, 6.56it/s] 13%|█▎ | 3/23 [00:00<00:03, 6.52it/s] 17%|█▋ | 4/23 [00:00<00:02, 6.50it/s] 22%|██▏ | 5/23 [00:00<00:02, 6.47it/s] 26%|██▌ | 6/23 [00:00<00:02, 6.37it/s] 30%|███ | 7/23 [00:01<00:02, 6.30it/s] 35%|███▍ | 8/23 [00:01<00:02, 6.32it/s] 39%|███▉ | 9/23 [00:01<00:02, 6.36it/s] 43%|████▎ | 10/23 [00:01<00:02, 6.30it/s] 48%|████▊ | 11/23 [00:01<00:01, 6.33it/s] 52%|█████▏ | 12/23 [00:01<00:01, 6.34it/s] 57%|█████▋ | 13/23 [00:02<00:01, 6.29it/s] 61%|██████ | 14/23 [00:02<00:01, 6.30it/s] 65%|██████▌ | 15/23 [00:02<00:01, 6.33it/s] 70%|██████▉ | 16/23 [00:02<00:01, 6.36it/s] 74%|███████▍ | 17/23 [00:02<00:00, 6.39it/s] 78%|███████▊ | 18/23 [00:02<00:00, 6.38it/s] 83%|████████▎ | 19/23 [00:02<00:00, 6.32it/s] 87%|████████▋ | 20/23 [00:03<00:00, 6.31it/s] 91%|█████████▏| 21/23 [00:03<00:00, 6.33it/s] 96%|█████████▌| 22/23 [00:03<00:00, 6.36it/s] 100%|██████████| 23/23 [00:03<00:00, 6.39it/s] 100%|██████████| 23/23 [00:03<00:00, 6.37it/s] Decoding latents in cuda:0... done in 0.41s Move latents to cpu... done in 0.0s Finished.