Girl by the Window with Light & Shadow
Input
prompt
Specify things to see in the output
(masterpiece, best quality), Re=L Rayford, short hair with long locks, blue hair, ponytail, blue eyes, red ribbon, sidelocks, ahoge, school uniform, suspenders, blue capelet, white shirt, blue choker, choker, miniskirt, white skirt, navel, gloves, dream like, looking at viewer, AGGA_ST012, disdainful eyes, natural lighting, sunset, window, cinematic, movie still, <lora:FaceBeauty_qinglong_V3:1>
negative_prompt
Specify things to not see in the output
(nsfw:1.3), bad_prompt_version2-neg, bad-hands-5 , EasyNegative V2, (worst quality:2), (low quality:2), (normal quality:2), lowres, watermark, lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature,
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.
498398697
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++ 3M SDE Karras
samping_steps
Number of denoising steps
55
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)
embedding_2
Embedding file (textural inversion). Apply by writing the following in prompt or negative prompt: (FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE)
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/ae04af8b8cca40909420d464f8383c9a/00000-498398697.webp
https://files.tungsten.run/uploads/3c64a8582f5843e49a30f2ef9b0755b3/00001-498398698.webp
https://files.tungsten.run/uploads/53e7ae1035b34118b1bf5125b23b8496/00002-498398699.webp
https://files.tungsten.run/uploads/1dd4a729cf294b3380be82f8a834667e/00003-498398700.webp
Finished in 153.5 seconds
Setting up the model... Processing... Loading VAE weight: models/VAE/blessed2_fp16.safetensors Full prompt: (masterpiece, best quality), Re=L Rayford, short hair with long locks, blue hair, ponytail, blue eyes, red ribbon, sidelocks, ahoge, school uniform, suspenders, blue capelet, white shirt, blue choker, choker, miniskirt, white skirt, navel, gloves, dream like, looking at viewer, AGGA_ST012, disdainful eyes, natural lighting, sunset, window, cinematic, movie still, <lora:FaceBeauty_qinglong_V3:1> Full negative prompt: (nsfw:1.3), bad_prompt_version2-neg, bad-hands-5 , EasyNegative V2, (worst quality:2), (low quality:2), (normal quality:2), lowres, watermark, lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, 0%| | 0/55 [00:00<?, ?it/s] 2%|▏ | 1/55 [00:01<01:42, 1.89s/it] 4%|▎ | 2/55 [00:03<01:37, 1.84s/it] 5%|▌ | 3/55 [00:05<01:36, 1.85s/it] 7%|▋ | 4/55 [00:07<01:36, 1.89s/it] 9%|▉ | 5/55 [00:09<01:34, 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1.47s/it] 96%|█████████▋| 53/55 [01:29<00:02, 1.45s/it] 98%|█████████▊| 54/55 [01:30<00:01, 1.25s/it] 100%|██████████| 55/55 [01:31<00:00, 1.07s/it] 100%|██████████| 55/55 [01:31<00:00, 1.66s/it] Decoding latents in cuda:0... done in 0.99s Move latents to cpu... done in 0.02s 0: 640x640 1 face, 8.0ms Speed: 3.5ms preprocess, 8.0ms inference, 25.2ms postprocess per image at shape (1, 3, 640, 640) 0%| | 0/31 [00:00<?, ?it/s] 3%|▎ | 1/31 [00:00<00:17, 1.76it/s] 6%|▋ | 2/31 [00:00<00:14, 2.05it/s] 10%|▉ | 3/31 [00:01<00:12, 2.25it/s] 13%|█▎ | 4/31 [00:01<00:11, 2.38it/s] 16%|█▌ | 5/31 [00:02<00:10, 2.40it/s] 19%|█▉ | 6/31 [00:02<00:10, 2.47it/s] 23%|██▎ | 7/31 [00:02<00:09, 2.48it/s] 26%|██▌ | 8/31 [00:03<00:09, 2.52it/s] 29%|██▉ | 9/31 [00:03<00:08, 2.50it/s] 32%|███▏ | 10/31 [00:04<00:08, 2.54it/s] 35%|███▌ | 11/31 [00:04<00:07, 2.53it/s] 39%|███▊ | 12/31 [00:04<00:07, 2.48it/s] 42%|████▏ | 13/31 [00:05<00:07, 2.51it/s] 45%|████▌ | 14/31 [00:05<00:06, 2.61it/s] 48%|████▊ | 15/31 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81%|████████ | 25/31 [00:09<00:02, 2.54it/s] 84%|████████▍ | 26/31 [00:10<00:01, 2.71it/s] 87%|████████▋ | 27/31 [00:10<00:01, 2.86it/s] 90%|█████████ | 28/31 [00:10<00:01, 2.91it/s] 94%|█████████▎| 29/31 [00:11<00:00, 2.93it/s] 97%|█████████▋| 30/31 [00:11<00:00, 3.40it/s] 100%|██████████| 31/31 [00:11<00:00, 4.01it/s] 100%|██████████| 31/31 [00:11<00:00, 2.72it/s] Decoding latents in cuda:0... done in 0.24s Move latents to cpu... done in 0.0s 0: 640x640 1 face, 7.6ms Speed: 2.9ms preprocess, 7.6ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640) 0%| | 0/31 [00:00<?, ?it/s] 3%|▎ | 1/31 [00:00<00:12, 2.44it/s] 6%|▋ | 2/31 [00:00<00:12, 2.38it/s] 10%|▉ | 3/31 [00:01<00:11, 2.44it/s] 13%|█▎ | 4/31 [00:01<00:11, 2.45it/s] 16%|█▌ | 5/31 [00:02<00:10, 2.45it/s] 19%|█▉ | 6/31 [00:02<00:09, 2.53it/s] 23%|██▎ | 7/31 [00:02<00:09, 2.45it/s] 26%|██▌ | 8/31 [00:03<00:09, 2.47it/s] 29%|██▉ | 9/31 [00:03<00:09, 2.43it/s] 32%|███▏ | 10/31 [00:04<00:08, 2.48it/s] 35%|███▌ | 11/31 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=========================================== A tensor with all NaNs was produced in VAE. Converted VAE into 32-bit float and retry. =========================================== done in 0.44s Move latents to cpu... done in 0.23s 0: 640x640 1 face, 7.6ms Speed: 2.8ms preprocess, 7.6ms inference, 1.7ms postprocess per image at shape (1, 3, 640, 640) 0%| | 0/31 [00:00<?, ?it/s] 3%|▎ | 1/31 [00:00<00:12, 2.44it/s] 6%|▋ | 2/31 [00:00<00:12, 2.36it/s] 10%|▉ | 3/31 [00:01<00:11, 2.43it/s] 13%|█▎ | 4/31 [00:01<00:10, 2.49it/s] 16%|█▌ | 5/31 [00:02<00:10, 2.47it/s] 19%|█▉ | 6/31 [00:02<00:09, 2.53it/s] 23%|██▎ | 7/31 [00:02<00:09, 2.49it/s] 26%|██▌ | 8/31 [00:03<00:09, 2.51it/s] 29%|██▉ | 9/31 [00:03<00:08, 2.48it/s] 32%|███▏ | 10/31 [00:04<00:08, 2.52it/s] 35%|███▌ | 11/31 [00:04<00:07, 2.51it/s] 39%|███▊ | 12/31 [00:04<00:07, 2.46it/s] 42%|████▏ | 13/31 [00:05<00:07, 2.48it/s] 45%|████▌ | 14/31 [00:05<00:06, 2.59it/s] 48%|████▊ | 15/31 [00:05<00:05, 2.71it/s] 52%|█████▏ | 16/31 [00:06<00:05, 2.77it/s] 55%|█████▍ | 17/31 [00:06<00:05, 2.74it/s] 58%|█████▊ | 18/31 [00:07<00:04, 2.65it/s] 61%|██████▏ | 19/31 [00:07<00:04, 2.64it/s] 65%|██████▍ | 20/31 [00:07<00:04, 2.68it/s] 68%|██████▊ | 21/31 [00:08<00:03, 2.69it/s] 71%|███████ | 22/31 [00:08<00:03, 2.61it/s] 74%|███████▍ | 23/31 [00:08<00:03, 2.65it/s] 77%|███████▋ | 24/31 [00:09<00:02, 2.71it/s] 81%|████████ | 25/31 [00:09<00:02, 2.60it/s] 84%|████████▍ | 26/31 [00:10<00:01, 2.76it/s] 87%|████████▋ | 27/31 [00:10<00:01, 2.90it/s] 90%|█████████ | 28/31 [00:10<00:01, 2.93it/s] 94%|█████████▎| 29/31 [00:10<00:00, 2.96it/s] 97%|█████████▋| 30/31 [00:11<00:00, 3.43it/s] 100%|██████████| 31/31 [00:11<00:00, 4.04it/s] 100%|██████████| 31/31 [00:11<00:00, 2.74it/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
(masterpiece, best quality), Re=L Rayford, short hair with long locks, blue hair, ponytail, blue eyes, red ribbon, sidelocks, ahoge, school uniform, suspenders, blue capelet, white shirt, blue choker, choker, miniskirt, white skirt, navel, gloves, dream like, looking at viewer, AGGA_ST012, disdainful eyes, natural lighting, sunset, window, cinematic, movie still, <lora:FaceBeauty_qinglong_V3:1>
negative_prompt
Specify things to not see in the output
(nsfw:1.3), bad_prompt_version2-neg, bad-hands-5 , EasyNegative V2, (worst quality:2), (low quality:2), (normal quality:2), lowres, watermark, lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature,
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.
498398697
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++ 3M SDE Karras
samping_steps
Number of denoising steps
55
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)
embedding_2
Embedding file (textural inversion). Apply by writing the following in prompt or negative prompt: (FILE_NAME_WITHOUT_EXTENSION:MAGNITUDE)
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/ae04af8b8cca40909420d464f8383c9a/00000-498398697.webp
https://files.tungsten.run/uploads/3c64a8582f5843e49a30f2ef9b0755b3/00001-498398698.webp
https://files.tungsten.run/uploads/53e7ae1035b34118b1bf5125b23b8496/00002-498398699.webp
https://files.tungsten.run/uploads/1dd4a729cf294b3380be82f8a834667e/00003-498398700.webp
Finished in 153.5 seconds
Setting up the model... Processing... Loading VAE weight: models/VAE/blessed2_fp16.safetensors Full prompt: (masterpiece, best quality), Re=L Rayford, short hair with long locks, blue hair, ponytail, blue eyes, red ribbon, sidelocks, ahoge, school uniform, suspenders, blue capelet, white shirt, blue choker, choker, miniskirt, white skirt, navel, gloves, dream like, looking at viewer, AGGA_ST012, disdainful eyes, natural lighting, sunset, window, cinematic, movie still, <lora:FaceBeauty_qinglong_V3:1> Full negative prompt: (nsfw:1.3), bad_prompt_version2-neg, bad-hands-5 , EasyNegative V2, (worst quality:2), (low quality:2), (normal quality:2), lowres, watermark, lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, 0%| | 0/55 [00:00<?, ?it/s] 2%|▏ | 1/55 [00:01<01:42, 1.89s/it] 4%|▎ | 2/55 [00:03<01:37, 1.84s/it] 5%|▌ | 3/55 [00:05<01:36, 1.85s/it] 7%|▋ | 4/55 [00:07<01:36, 1.89s/it] 9%|▉ | 5/55 [00:09<01:34, 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1.47s/it] 96%|█████████▋| 53/55 [01:29<00:02, 1.45s/it] 98%|█████████▊| 54/55 [01:30<00:01, 1.25s/it] 100%|██████████| 55/55 [01:31<00:00, 1.07s/it] 100%|██████████| 55/55 [01:31<00:00, 1.66s/it] Decoding latents in cuda:0... done in 0.99s Move latents to cpu... done in 0.02s 0: 640x640 1 face, 8.0ms Speed: 3.5ms preprocess, 8.0ms inference, 25.2ms postprocess per image at shape (1, 3, 640, 640) 0%| | 0/31 [00:00<?, ?it/s] 3%|▎ | 1/31 [00:00<00:17, 1.76it/s] 6%|▋ | 2/31 [00:00<00:14, 2.05it/s] 10%|▉ | 3/31 [00:01<00:12, 2.25it/s] 13%|█▎ | 4/31 [00:01<00:11, 2.38it/s] 16%|█▌ | 5/31 [00:02<00:10, 2.40it/s] 19%|█▉ | 6/31 [00:02<00:10, 2.47it/s] 23%|██▎ | 7/31 [00:02<00:09, 2.48it/s] 26%|██▌ | 8/31 [00:03<00:09, 2.52it/s] 29%|██▉ | 9/31 [00:03<00:08, 2.50it/s] 32%|███▏ | 10/31 [00:04<00:08, 2.54it/s] 35%|███▌ | 11/31 [00:04<00:07, 2.53it/s] 39%|███▊ | 12/31 [00:04<00:07, 2.48it/s] 42%|████▏ | 13/31 [00:05<00:07, 2.51it/s] 45%|████▌ | 14/31 [00:05<00:06, 2.61it/s] 48%|████▊ | 15/31 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81%|████████ | 25/31 [00:09<00:02, 2.54it/s] 84%|████████▍ | 26/31 [00:10<00:01, 2.71it/s] 87%|████████▋ | 27/31 [00:10<00:01, 2.86it/s] 90%|█████████ | 28/31 [00:10<00:01, 2.91it/s] 94%|█████████▎| 29/31 [00:11<00:00, 2.93it/s] 97%|█████████▋| 30/31 [00:11<00:00, 3.40it/s] 100%|██████████| 31/31 [00:11<00:00, 4.01it/s] 100%|██████████| 31/31 [00:11<00:00, 2.72it/s] Decoding latents in cuda:0... done in 0.24s Move latents to cpu... done in 0.0s 0: 640x640 1 face, 7.6ms Speed: 2.9ms preprocess, 7.6ms inference, 2.2ms postprocess per image at shape (1, 3, 640, 640) 0%| | 0/31 [00:00<?, ?it/s] 3%|▎ | 1/31 [00:00<00:12, 2.44it/s] 6%|▋ | 2/31 [00:00<00:12, 2.38it/s] 10%|▉ | 3/31 [00:01<00:11, 2.44it/s] 13%|█▎ | 4/31 [00:01<00:11, 2.45it/s] 16%|█▌ | 5/31 [00:02<00:10, 2.45it/s] 19%|█▉ | 6/31 [00:02<00:09, 2.53it/s] 23%|██▎ | 7/31 [00:02<00:09, 2.45it/s] 26%|██▌ | 8/31 [00:03<00:09, 2.47it/s] 29%|██▉ | 9/31 [00:03<00:09, 2.43it/s] 32%|███▏ | 10/31 [00:04<00:08, 2.48it/s] 35%|███▌ | 11/31 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=========================================== A tensor with all NaNs was produced in VAE. Converted VAE into 32-bit float and retry. =========================================== done in 0.44s Move latents to cpu... done in 0.23s 0: 640x640 1 face, 7.6ms Speed: 2.8ms preprocess, 7.6ms inference, 1.7ms postprocess per image at shape (1, 3, 640, 640) 0%| | 0/31 [00:00<?, ?it/s] 3%|▎ | 1/31 [00:00<00:12, 2.44it/s] 6%|▋ | 2/31 [00:00<00:12, 2.36it/s] 10%|▉ | 3/31 [00:01<00:11, 2.43it/s] 13%|█▎ | 4/31 [00:01<00:10, 2.49it/s] 16%|█▌ | 5/31 [00:02<00:10, 2.47it/s] 19%|█▉ | 6/31 [00:02<00:09, 2.53it/s] 23%|██▎ | 7/31 [00:02<00:09, 2.49it/s] 26%|██▌ | 8/31 [00:03<00:09, 2.51it/s] 29%|██▉ | 9/31 [00:03<00:08, 2.48it/s] 32%|███▏ | 10/31 [00:04<00:08, 2.52it/s] 35%|███▌ | 11/31 [00:04<00:07, 2.51it/s] 39%|███▊ | 12/31 [00:04<00:07, 2.46it/s] 42%|████▏ | 13/31 [00:05<00:07, 2.48it/s] 45%|████▌ | 14/31 [00:05<00:06, 2.59it/s] 48%|████▊ | 15/31 [00:05<00:05, 2.71it/s] 52%|█████▏ | 16/31 [00:06<00:05, 2.77it/s] 55%|█████▍ | 17/31 [00:06<00:05, 2.74it/s] 58%|█████▊ | 18/31 [00:07<00:04, 2.65it/s] 61%|██████▏ | 19/31 [00:07<00:04, 2.64it/s] 65%|██████▍ | 20/31 [00:07<00:04, 2.68it/s] 68%|██████▊ | 21/31 [00:08<00:03, 2.69it/s] 71%|███████ | 22/31 [00:08<00:03, 2.61it/s] 74%|███████▍ | 23/31 [00:08<00:03, 2.65it/s] 77%|███████▋ | 24/31 [00:09<00:02, 2.71it/s] 81%|████████ | 25/31 [00:09<00:02, 2.60it/s] 84%|████████▍ | 26/31 [00:10<00:01, 2.76it/s] 87%|████████▋ | 27/31 [00:10<00:01, 2.90it/s] 90%|█████████ | 28/31 [00:10<00:01, 2.93it/s] 94%|█████████▎| 29/31 [00:10<00:00, 2.96it/s] 97%|█████████▋| 30/31 [00:11<00:00, 3.43it/s] 100%|██████████| 31/31 [00:11<00:00, 4.04it/s] 100%|██████████| 31/31 [00:11<00:00, 2.74it/s] Decoding latents in cuda:0... done in 0.41s Move latents to cpu... done in 0.0s Finished.